/*For the second research question (change model), we used Bayesian linear regression to analyse whether the logarithmic k-values and ? were related to the delta of SRAD severity. We calculated delta as differences between SRAD symptoms and quantity-frequency-indices at follow-up minus baseline. We adjusted this comparison (difference of difference) for participants’ values at baseline (additional covariate). Predictors and outcomes were both z-standardized, yielding standardized regression coefficients that have the same range as correlations. Concerning the priors, we expected the associations to be greater than zero for delay discounting resp. lower than zero for the other tasks and we had the assumption that the associations of our laboratory tasks with later clinical symptoms and real-life behaviour would be no more than medium. Specifically, we assumed a probability of 95% that the true association will range between 0 and 0.5 (resp. -0.5 and 0) which corresponds with the expectation of 0.25 (-0.25) and standard deviation of 0.127 in a normal distribution. To find out whether the assumed association of impulsive decision-making and SRAD severity may only be present in the baseline disorder groups, we additionally analysed whether we can find the effects over all participants also separately within the baseline disorder groups using the same priors.*/ //SAD symptoms //1. DDP, positive association with later SAD symptoms //SUD symptoms bayes , rseed(64674376) prior({ std_symp_sud_delta: ddp_log_k_z }, normal(0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_sud_delta ddp_log_k_z std_bl_sud_symp bayestest interval {std_symp_sud_delta: ddp_log_k_z}, lower(0) upper(1) //ND symptoms bayes , rseed(64674376) prior({ std_symp_nd_delta: ddp_log_k_z }, normal(0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_nd_delta ddp_log_k_z std_bl_nd_symp bayestest interval {std_symp_nd_delta: ddp_log_k_z}, lower(0) upper(1) //2. PDL, negative association with later SAD symptoms //SUD symptoms bayes , rseed(64674376) prior({ std_symp_sud_delta: pdl_kN_z }, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_sud_delta pdl_kN_z std_bl_sud_symp bayestest interval {std_symp_sud_delta: pdl_kN_z}, lower(-1) upper(0) //ND symptoms bayes , rseed(64674376) prior({std_symp_nd_delta: pdl_kN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_nd_delta pdl_kN_z std_bl_nd_symp bayestest interval {std_symp_nd_delta: pdl_kN_z}, lower(-1) upper(0) //3. PDW, negative association with later SAD symptoms //SUD symptoms bayes , rseed(64674376) prior({ std_symp_sud_delta: pdw_kN_z }, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_sud_delta pdw_kN_z std_bl_sud_symp bayestest interval {std_symp_sud_delta: pdw_kN_z}, lower(-1) upper(0) //ND symptoms bayes , rseed(64674376) prior({ std_symp_nd_delta: pdw_kN_z }, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_nd_delta pdw_kN_z std_bl_nd_symp bayestest interval {std_symp_nd_delta: pdw_kN_z}, lower(-1) upper(0) //4. MG, negative association with later SAD symptoms //SUD symptoms bayes , rseed(64674376) prior({std_symp_sud_delta: mg_lN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_sud_delta mg_lN_z std_bl_sud_symp bayestest interval {std_symp_sud_delta: mg_lN_z}, lower(-1) upper(0) //ND symptoms bayes , rseed(64674376) prior({std_symp_nd_delta: mg_lN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_symp_nd_delta mg_lN_z std_bl_nd_symp bayestest interval {std_symp_nd_delta: mg_lN_z}, lower(-1) upper(0) //QFI //1. DDP //positive association with later SUD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_sud_delta: ddp_log_k_z}, normal(0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_sud_delta ddp_log_k_z std_bl_qfi_sud bayestest interval {std_bl_qfi_sud_delta:ddp_log_k_z}, lower(0) upper(1) // positive association with later NDD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_ba_delta: ddp_log_k_z}, normal(0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_ba_delta ddp_log_k_z std_bl_qfi_ba bayestest interval {std_bl_qfi_ba_delta:ddp_log_k_z}, lower(0) upper(1) //2. PDL //negative association with later SUD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_sud_delta: pdl_kN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_sud_delta pdl_kN_z std_bl_qfi_sud bayestest interval {std_bl_qfi_sud_delta:pdl_kN_z}, lower(-1) upper(0) //negative association with later NDD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_ba_delta: pdl_kN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_ba_delta pdl_kN_z std_bl_qfi_ba bayestest interval {std_bl_qfi_ba_delta:pdl_kN_z}, lower(-1) upper(0) //PDW, negativ mit QFI //negative association with later SUD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_sud_delta: pdw_kN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_sud_delta pdw_kN_z std_bl_qfi_sud bayestest interval {std_bl_qfi_sud_delta:pdw_kN_z}, lower(-1) upper(0) //negative association with later NDD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_ba_delta: pdw_kN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_ba_delta pdw_kN_z std_bl_qfi_ba bayestest interval {std_bl_qfi_ba_delta:pdw_kN_z}, lower(-1) upper(0) //MG, negativ mit QFI //negative association with later SUD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_sud_delta: mg_lN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_sud_delta mg_lN_z std_bl_qfi_sud bayestest interval {std_bl_qfi_sud_delta:mg_lN_z}, lower(-1) upper(0) //negative association with later NDD-related QFI bayes , rseed(64674376) prior({std_bl_qfi_ba_delta: mg_lN_z}, normal(-0.25,.016)) mcmcsize(100000) burnin(5000) thinning(2): regress std_bl_qfi_ba_delta mg_lN_z std_bl_qfi_ba bayestest interval {std_bl_qfi_ba_delta:mg_lN_z}, lower(-1) upper(0)