************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************ *Prepared by Adam Fine on 4.8.20 (#0) *Adapted by CPRF on 1/09/2020 (#1) *Revised by CPRF on 8/6/2021, for revision PLOS ONE (#2) ************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************ *Dataset log using "C:\Users\creinde\OneDrive - UvA\RESEARCH\2020\20 03 Coronavirus-measures compliance survey\Data\US\NWO US Summer data\Corona Compliance survey US W1-W3 LOG R1.smcl" use "C:\Users\creinde\OneDrive - UvA\RESEARCH\2020\20 03 Coronavirus-measures compliance survey\Data\US\NWO US Summer data\Corona Compliance survey US W1-3 May-July.dta" ************************************************************************************** ************************************************************************************** *A. SELECTION CRITERION: * - Only if provided consent * - No missing data * - Both checks correct * - Nonbinary gender excluded (insufficient number) gen chris_sample_reqs = 1 if Consent == 1 & N_Missing == 0 & NChecksRight == 2 & Gender < 3 *B. SELECTION CRITERION: * - Only if provided consent * - Both checks correct *gen chris_sample_reqs = 1 if Consent == 1 & NChecksRight == 2 *C. SELECTION CRITERION: * - Only if provided consent * - No missing data *gen chris_sample_reqs = 1 if Consent == 1 & N_Missing == 0 tab chris_sample_reqs *generate wave dummies gen wave_d1 = 0 replace wave_d1 = 1 if (WAVE == 2) gen wave_d2 = 0 replace wave_d2 = 1 if (WAVE == 3) ************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************ *HIERARCHICAL MODEL ************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************ *1. Step 1: covariates only *1.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 if chris_sample_reqs == 1 *1.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 if chris_sample_reqs == 1 estimates store model_1 *1.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *1.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *1.a.5. Effect size estat esize *1.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 if chris_sample_reqs == 1, vce(ro) ***************** *2. Step 2: Add practical knowledge and understanding *2.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear if chris_sample_reqs == 1 *2.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear if chris_sample_reqs == 1 estimates store model_2 *2.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *2.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *2.a.5. Effect size estat esize *2.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear if chris_sample_reqs == 1, vce(ro) ***************** *3. Step 3: Add costs + benefits *3.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe if chris_sample_reqs == 1 *3.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe if chris_sample_reqs == 1 estimates store model_3 *3.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *3.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *3.a.5. Effect size estat esize *3.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe if chris_sample_reqs == 1, vce(ro) ***************** *4. Step 4: Add legitimacy *4.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 if chris_sample_reqs == 1 *4.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 if chris_sample_reqs == 1 estimates store model_4 *4.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *4.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *4.a.5. Effect size estat esize *4.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 if chris_sample_reqs == 1, vce(ro) ***************** *5. Step 5: Add personal factors *5.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 if chris_sample_reqs == 1 *5.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 if chris_sample_reqs == 1 estimates store model_5 *5.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *5.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *5.a.5. Effect size estat esize *5.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 if chris_sample_reqs == 1, vce(ro) ***************** *6. Step 6: Add social environment *6.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 if chris_sample_reqs == 1 *6.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 if chris_sample_reqs == 1 estimates store model_6 *6.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *6.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *6.a.5. Effect size estat esize *6.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 if chris_sample_reqs == 1, vce(ro) ***************** *7. Step 7: Add practical circumstances *7.a.1 Descriptive Statistics sum DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 if chris_sample_reqs == 1 *7.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 if chris_sample_reqs == 1 estimates store model_7 *7.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *7.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *7.a.5. Effect size estat esize *7.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 if chris_sample_reqs == 1, vce(ro) ***************** *8. Compare Rsq models *8.a.1. model 1 vs model 2 lrtest model_1 model_2 *8.a.2. model 2 vs model 3 lrtest model_2 model_3 *8.a.3. model 3 vs model 4 lrtest model_3 model_4 *8.a.4. model 4 vs model 5 lrtest model_4 model_5 *8.a.5. model 5 vs model 6 lrtest model_5 model_6 *8.a.6. model 6 vs model 7 lrtest model_6 model_7 ************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************ *INTERACTIONS WITH SURVEY WAVE ************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************ *9. Model 9: Knowledge x Survey Wave *9.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 i.Current_measures##i.wave_d1 Current_measures##i.wave_d2 if chris_sample_reqs == 1 *9.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *9.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *9.a.5. Effect size estat esize *9.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 i.Current_measures##i.wave_d1 i.Current_measures##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *10. Model 10: Clarity x Survey Wave *10.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Measures_clear##i.wave_d1 c.Measures_clear##i.wave_d2 if chris_sample_reqs == 1 *10.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *10.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *10.a.5. Effect size estat esize *10.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Measures_clear##i.wave_d1 c.Measures_clear##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *11. Model 11: Perceived threat x Survey Wave *11.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.MA_Perc_Threat_SC3##i.wave_d1 c.MA_Perc_Threat_SC3##i.wave_d2 if chris_sample_reqs == 1 *11.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *11.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *11.a.5. Effect size estat esize *11.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.MA_Perc_Threat_SC3##i.wave_d1 c.MA_Perc_Threat_SC3##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *12. Model 12: Costs x Survey Wave *12.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Costs_SC5##i.wave_d1 c.Costs_SC5##i.wave_d2 if chris_sample_reqs == 1 *12.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *12.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *12.a.5. Effect size estat esize *12.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Costs_SC5##i.wave_d1 c.Costs_SC5##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *13. Model 13: Punish certainty x Survey Wave *13.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Deterr_SD_Likely_SC2##i.wave_d1 c.Deterr_SD_Likely_SC2##i.wave_d2 if chris_sample_reqs == 1 *13.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *13.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *13.a.5. Effect size estat esize *13.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Deterr_SD_Likely_SC2##i.wave_d1 c.Deterr_SD_Likely_SC2##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *14. Model 14: Punish severity x Survey Wave *14.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Deterr_SD_Severe##i.wave_d1 c.Deterr_SD_Severe##i.wave_d2 if chris_sample_reqs == 1 *14.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *14.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *14.a.5. Effect size estat esize *14.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Deterr_SD_Severe##i.wave_d1 c.Deterr_SD_Severe##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *15. Model 15: Moral alignment x Survey Wave *15.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.MA_MoralBelief##i.wave_d1 c.MA_MoralBelief##i.wave_d2 if chris_sample_reqs == 1 *15.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *15.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *15.a.5. Effect size estat esize *15.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.MA_MoralBelief##i.wave_d1 c.MA_MoralBelief##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *16. Model 16: Authority evaluation x Survey Wave *16.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.MA_Authority_SC2##i.wave_d1 c.MA_Authority_SC2##i.wave_d2 if chris_sample_reqs == 1 *16.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *16.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *16.a.5. Effect size estat esize *16.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.MA_Authority_SC2##i.wave_d1 c.MA_Authority_SC2##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *17. Model 17: Normative obligation x Survey Wave *17.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NOO_SC3##i.wave_d1 c.NOO_SC3##i.wave_d2 if chris_sample_reqs == 1 *17.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *17.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *17.a.5. Effect size estat esize *17.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NOO_SC3##i.wave_d1 c.NOO_SC3##i.wave_d2 if chris_sample_reqs == 1, vce(ro) *17.a.7 Simple main effects reg DV_Compliance_SC7 i.WAVE Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NOO_SC3##i.WAVE if chris_sample_reqs == 1, vce(ro) margins WAVE, dydx(NOO_SC3) margins WAVE, dydx(NOO_SC3) pwcompare(effects) ***************** *18. Model 18: Non-normative obligation x Survey Wave *18.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NNOO_SC3##i.wave_d1 c.NNOO_SC3##i.wave_d2 if chris_sample_reqs == 1 *18.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *18.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *18.a.5. Effect size estat esize *18.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NNOO_SC3##i.wave_d1 c.NNOO_SC3##i.wave_d2 if chris_sample_reqs == 1, vce(ro) *18.a.7 Simple main effects reg DV_Compliance_SC7 i.WAVE Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NNOO_SC3##i.WAVE if chris_sample_reqs == 1, vce(ro) margins WAVE, dydx(NNOO_SC3) margins WAVE, dydx(NNOO_SC3) pwcompare(effects) ***************** *19. Model 19: PJ x Survey Wave *19.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.PJE_SC4##i.wave_d1 c.PJE_SC4##i.wave_d2 if chris_sample_reqs == 1 *19.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *19.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *19.a.5. Effect size estat esize *19.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.PJE_SC4##i.wave_d1 c.PJE_SC4##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *20. Model 20: Trust in science x Survey Wave *20.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Trust_Science_SC4##i.wave_d1 c.Trust_Science_SC4##i.wave_d2 if chris_sample_reqs == 1 *20.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *20.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *20.a.5. Effect size estat esize *20.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Trust_Science_SC4##i.wave_d1 c.Trust_Science_SC4##i.wave_d2 if chris_sample_reqs == 1, vce(ro) *20.a.7 Simple main effects reg DV_Compliance_SC7 i.WAVE Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Trust_Science_SC4##i.WAVE if chris_sample_reqs == 1, vce(ro) margins WAVE, dydx(Trust_Science_SC4) margins WAVE, dydx(Trust_Science_SC4) pwcompare(effects) ***************** *21. Model 21: Trust in media x Survey Wave *21.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Trust_in_media##i.wave_d1 c.Trust_in_media##i.wave_d2 if chris_sample_reqs == 1 *21.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *21.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *21.a.5. Effect size estat esize *21.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Trust_in_media##i.wave_d1 c.Trust_in_media##i.wave_d2 if chris_sample_reqs == 1, vce(ro) *21.a.7 Simple main effects reg DV_Compliance_SC7 i.WAVE Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Trust_in_media##i.WAVE if chris_sample_reqs == 1, vce(ro) margins WAVE, dydx(Trust_in_media) margins WAVE, dydx(Trust_in_media) pwcompare(effects) ***************** *22. Model 22: Obligation to obey the law x Survey Wave *22.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.OOL_SC12##i.wave_d1 c.OOL_SC12##i.wave_d2 if chris_sample_reqs == 1 *22.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *22.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *22.a.5. Effect size estat esize *22.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.OOL_SC12##i.wave_d1 c.OOL_SC12##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *23. Model 23: Impulsivity x Survey Wave *23.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Impulsivity_SC4##i.wave_d1 c.Impulsivity_SC4##i.wave_d2 if chris_sample_reqs == 1 *23.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *23.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *23.a.5. Effect size estat esize *23.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Impulsivity_SC4##i.wave_d1 c.Impulsivity_SC4##i.wave_d2 if chris_sample_reqs == 1, vce(ro) *21.a.7 Simple main effects reg DV_Compliance_SC7 i.WAVE Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.Impulsivity_SC4##i.WAVE if chris_sample_reqs == 1, vce(ro) margins WAVE, dydx(Impulsivity_SC4) margins WAVE, dydx(Impulsivity_SC4) pwcompare(effects) ***************** *24. Model 24: Neg emotions x Survey Wave *24.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NegEmo_SC6##i.wave_d1 c.NegEmo_SC6##i.wave_d2 if chris_sample_reqs == 1 *24.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *24.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *24.a.5. Effect size estat esize *24.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.NegEmo_SC6##i.wave_d1 c.NegEmo_SC6##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *25. Model 25: Social norms x Survey Wave *25.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.SN_SC7##i.wave_d1 c.SN_SC7##i.wave_d2 if chris_sample_reqs == 1 *25.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *25.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *25.a.5. Effect size estat esize *25.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.SN_SC7##i.wave_d1 c.SN_SC7##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *26. Model 26: Capacity x Survey Wave *26.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.CTC_SC7##i.wave_d1 c.CTC_SC7##i.wave_d2 if chris_sample_reqs == 1 *26.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *26.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *26.a.5. Effect size estat esize *26.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.CTC_SC7##i.wave_d1 c.CTC_SC7##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *27. Model 27: Opportunity x Survey Wave *27.a.2 Regression reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.OTC_SC7##i.wave_d1 c.OTC_SC7##i.wave_d2 if chris_sample_reqs == 1 *27.a.3 Check hettest: Run this right after your regression to apply the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity. *if significant, then you need to run the regression with vce(ro) at the end estat hettest *27.a.4. check vif, to check for for multicollinearity (VIFs >10 are problematic) vif *27.a.5. Effect size estat esize *27.a.6 Regression with vce(ro) reg DV_Compliance_SC7 i.wave_d1 i.wave_d2 Age i.Gender_Female i.Minority Education i.Employed i.Corona_care i.Insurance_Public i.Insurance_Private SES_before SES_change i.Health_self i.Health_other i.Conservative_01 i.Conservative_other i.GeoCensus_d1 i.GeoCensus_d2 i.GeoCensus_d3 i.Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7 c.OTC_SC7##i.wave_d1 c.OTC_SC7##i.wave_d2 if chris_sample_reqs == 1, vce(ro) ***************** *28. Mediation model *28.a.0 Install paramed package ssc install paramed help paramed *28.a.1 Mediation model, wave (1-2) on compliance mediated by knowledge paramed DV_Compliance_SC7, avar(wave_d1) mvar(Current_measures) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(logistic) nointer boot seed(1234) *28.a.2 Mediation model, wave (1-3) on compliance mediated by knowledge paramed DV_Compliance_SC7, avar(wave_d2) mvar(Current_measures) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(logistic) nointer boot seed(1234) *28.b.1 Mediation model, wave (1-2) on compliance mediated by perceived threat paramed DV_Compliance_SC7, avar(wave_d1) mvar(MA_Perc_Threat_SC3) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.b.2 Mediation model, wave (1-3) on compliance mediated by perceived threat paramed DV_Compliance_SC7, avar(wave_d2) mvar(MA_Perc_Threat_SC3) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.c.1 Mediation model, wave (1-2) on compliance mediated by costs paramed DV_Compliance_SC7, avar(wave_d1) mvar(Costs_SC5) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.c.2 Mediation model, wave (1-3) on compliance mediated by costs paramed DV_Compliance_SC7, avar(wave_d2) mvar(Costs_SC5) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.d.1 Mediation model, wave (1-2) on compliance mediated by moral alignment paramed DV_Compliance_SC7, avar(wave_d1) mvar(MA_MoralBelief) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.d.2 Mediation model, wave (1-3) on compliance mediated by moral alignment paramed DV_Compliance_SC7, avar(wave_d2) mvar(MA_MoralBelief) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.e.1 Mediation model, wave (1-2) on compliance mediated by social norms paramed DV_Compliance_SC7, avar(wave_d1) mvar(SN_SC7) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.e.2 Mediation model, wave (1-3) on compliance mediated by social norms paramed DV_Compliance_SC7, avar(wave_d2) mvar(SN_SC7) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 CTC_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.f.1 Mediation model, wave (1-2) on compliance mediated by capacity paramed DV_Compliance_SC7, avar(wave_d1) mvar(CTC_SC7) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.f.2 Mediation model, wave (1-3) on compliance mediated by capacity paramed DV_Compliance_SC7, avar(wave_d2) mvar(CTC_SC7) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 OTC_SC7) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.g.1 Mediation model, wave (1-2) on compliance mediated by opportunity paramed DV_Compliance_SC7, avar(wave_d1) mvar(OTC_SC7) cvars(wave_d2 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 ) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) *28.g.2 Mediation model, wave (1-3) on compliance mediated by opportunity paramed DV_Compliance_SC7, avar(wave_d2) mvar(OTC_SC7) cvars(wave_d1 Age Gender_Female Minority Education Employed Corona_care Insurance_Public Insurance_Private SES_before SES_change Health_self Health_other Conservative_01 Conservative_other GeoCensus_d1 GeoCensus_d2 GeoCensus_d3 Current_measures Measures_clear MA_Perc_Threat_SC3 Costs_SC5 Deterr_SD_Likely_SC2 Deterr_SD_Severe MA_MoralBelief MA_Authority_SC2 NOO_SC3 NNOO_SC3 OOL_SC12 PJE_SC4 Trust_Science_SC4 Trust_in_media Impulsivity_SC4 NegEmo_SC6 SN_SC7 CTC_SC7 ) a0(0) a1(1) m(1) yreg(linear) mreg(linear) nointer boot seed(1234) ***************** log close clear exit *End of do file ************************************************************************************ ************************************************************************************ ************************************************************************************ ************************************************************************************