Primärdaten zur Studie "Sensitivity analyses for data missing at random versus missing not at random using Latent Growth Modelling: A practical guide for randomised controlled trials"

Staudt, Andreas

Baumann, Sophie

2022-09-08T13:28:59Z

2022-09-08T13:28:59Z

2022

Die Daten entstammen der PRINT-Studie ("Überprüfung einer proaktiven Expertensystemintervention zur Prävention und Beendigung von riskantem Alkoholkonsum"), einer randomisiert-kontrollierten Interventionsstudie. Die Stichprobe aus Alkoholkonsument*innen aus der Allgemeinbevölkerung (N = 1646) wurde zufällig in Interventions- und Kontrollgruppe aufgeteilt. In die Studie wurden alle Alkoholkonsument*innen eingeschlossen, unabhängig von der Konsummenge. AlleStudienteilnehmer*innen wurden zu Baseline, nach 3, 6, 12 und 36 Monaten standardisiert befragt. Die Interventionsgruppe erhielt drei individualisierte Feedbackbriefe zu Baseline, nach 3 und 6 Monaten. Die Briefe wurden automatisch von einem computerbasierten Expertensystem nach vorher definierten Entscheidungsregeln zusammengestellt und basierten auf den Selbstberichtsangaben der Studienteilnehmer*innen zu den jeweiligen Messzeitpunkten. Die Briefe enthielten individualisierte Rückmeldungen zum Alkoholkonsum, zum alkoholbezogenen Risiko, zur Veränderungsmotivation sowie zu weiteren psychologischen Variablen (Selbstwirksamkeit, Entscheidungsbalance, Verhaltensänderungsstrategien). Die Intervention basierte auf dem Transtheoretischen Modell der Verhaltensänderung. Die Kontrollgruppe erhielt keinerlei Rückmeldungen. Das Ziel war eine Reduktion der durchschnittlichen Trinkmenge nach 12 bzw. 36 Monaten.

The data come from the PRINT study ("Testing a proactive expert system intervention to prevent and to quit at-risk alcohol use"), a randomized controlled trial. The sample of alcohol consumers from the general population (N = 1646) was randomized into an intervention and control group. All alcohol consumers were included in the study, regardless of the amount consumed. Standardized assessments took place at baseline, 3, 6, 12 and 36 months. The intervention group received three individualized feedback letters at baseline, after 3 and 6 months. The letters were automatically compiled by a computer-based expert system according to predefined decision rules and were based on the self-report data of the study participants at the respective measurement points. The letters contained individualized feedback on alcohol consumption, alcohol-related risk, motivation to change and other psychological variables (self-efficacy, decision balance, behavior change strategies). The intervention was based on the Transtheoretical Model of Behavior Change. The control group did not receive any feedback. The aim was to reduce the average amount of drinking after 12 or 36 months.

stas21pr11_readme.txt: Beschreibung der vorliegenden Dateien;stas21pr11_pd.txt: Primärdatensatz;stas21pr11_kb.txt: Kodebuch zum Primärdatensatz stas21pr11_pd.txt;1a_uncond_lgm_linear.inp.txt: MPlus Syntax 1a input - Preliminary model with linear growth factor;1a_uncond_lgm_linear.out.txt: MPlus Syntax 1a output - Preliminary model with linear growth factor;1b_uncond_lgm_quadratic.inp.txt: MPlus Syntax 1b input - Preliminary model with quadratic growth factor;1b_uncond_lgm_quadratic.out.txt: MPlus Syntax 1b output - Preliminary model with quadratic growth factor;1c_uncond_lgm_cubic.inp.txt: MPlus Syntax 1c input - Preliminary model with cubic growth factor;1c_uncond_lgm_cubic.out.txt: Mplus Syntax 1c output - Preliminary model with cubic growth factor;2a_unadj_mar_model.inp.txt: MPlus Syntax 2a input - Unadjusted MAR model;2a_unadj_mar_model.out.txt: MPlus Syntax 2a output - Unadjusted MAR model;2b_adj_mar_model.inp.txt: MPlus Syntax 2b input - Adjusted MAR model;2b_adj_mar_model.out.txt: MPlus Syntax 2b output - Adjusted MAR model;3a_dk_survival_indicators.inp.txt: MPlus Syntax 3a input - Diggle Kenward selection model with survival indicators;3a_dk_survival_indicators.out.txt: MPlus Syntax 3a output - Diggle Kenward selection model with survival indicators;3b_dk_multinomial_indicators.inp.txt: MPlus Syntax 3b input - Diggle Kenward selection model with multinomial missing indicators;3b_dk_multinomial_indicators.out.txt: MPlus Syntax 3b output - Diggle Kenward selection model with multinomial missing indicators;3c_wc_survival_indicators.inp.txt: MPlus Syntax 3c input - Wu Carroll shared parameter model with survival indicators;3c_wc_survival_indicators.out.txt: MPlus Syntax 3c output - Wu Carroll shared parameter model with survival indicators;3d_wc_multinomial_indicators.inp.txt: MPlus Syntax 3d input - Wu Carroll shared parameter model with multinomial indicators;3d_wc_multinomial_indicators.out.txt: MPlus Syntax 3d output - Wu Carroll shared parameter model with multinomial indicators;3e_pattern_mixture_cc.inp.txt: MPlus Syntax 3e input - Pattern mixture model with complete case missing variable restriction;3e_pattern_mixture_cc.out.txt: MPlus Syntax 3e output - Pattern mixture model with complete case missing variable restriction;3f_pattern_mixture_nc.inp.txt: MPlus Syntax 3f input - Pattern mixture model with neighbouring case missing variable restriction;3f_pattern_mixture_nc.out.txt: MPlus Syntax 3f output - Pattern mixture model with neighbouring case missing variable restriction;3g_pattern_mixture_ac.inp.txt: MPlus Syntax 3g input - Pattern mixture model with available case missing variable restriction;3g_pattern_mixture_ac.out.txt: MPlus Syntax 3g output - Pattern mixture model with available case missing variable restriction;

stas21pr11_readme.txt: Description of the files;stas21pr11_pd.txt: Primary data set;stas21pr11_kb.txt: Codebook to primary data set stas21pr11_pd.txt;1a_uncond_lgm_linear.inp.txt: MPlus Syntax 1a input - Preliminary model with linear growth factor;1a_uncond_lgm_linear.out.txt: MPlus Syntax 1a output - Preliminary model with linear growth factor;1b_uncond_lgm_quadratic.inp.txt: MPlus Syntax 1b input - Preliminary model with quadratic growth factor;1b_uncond_lgm_quadratic.out.txt: MPlus Syntax 1b output - Preliminary model with quadratic growth factor;1c_uncond_lgm_cubic.inp.txt: MPlus Syntax 1c input - Preliminary model with cubic growth factor;1c_uncond_lgm_cubic.out.txt: Mplus Syntax 1c output - Preliminary model with cubic growth factor;2a_unadj_mar_model.inp.txt: MPlus Syntax 2a input - Unadjusted MAR model;2a_unadj_mar_model.out.txt: MPlus Syntax 2a output - Unadjusted MAR model;2b_adj_mar_model.inp.txt: MPlus Syntax 2b input - Adjusted MAR model;2b_adj_mar_model.out.txt: MPlus Syntax 2b output - Adjusted MAR model;3a_dk_survival_indicators.inp.txt: MPlus Syntax 3a input - Diggle Kenward selection model with survival indicators;3a_dk_survival_indicators.out.txt: MPlus Syntax 3a output - Diggle Kenward selection model with survival indicators;3b_dk_multinomial_indicators.inp.txt: MPlus Syntax 3b input - Diggle Kenward selection model with multinomial missing indicators;3b_dk_multinomial_indicators.out.txt: MPlus Syntax 3b output - Diggle Kenward selection model with multinomial missing indicators;3c_wc_survival_indicators.inp.txt: MPlus Syntax 3c input - Wu Carroll shared parameter model with survival indicators;3c_wc_survival_indicators.out.txt: MPlus Syntax 3c output - Wu Carroll shared parameter model with survival indicators;3d_wc_multinomial_indicators.inp.txt: MPlus Syntax 3d input - Wu Carroll shared parameter model with multinomial indicators;3d_wc_multinomial_indicators.out.txt: MPlus Syntax 3d output - Wu Carroll shared parameter model with multinomial indicators;3e_pattern_mixture_cc.inp.txt: MPlus Syntax 3e input - Pattern mixture model with complete case missing variable restriction;3e_pattern_mixture_cc.out.txt: MPlus Syntax 3e output - Pattern mixture model with complete case missing variable restriction;3f_pattern_mixture_nc.inp.txt: MPlus Syntax 3f input - Pattern mixture model with neighbouring case missing variable restriction;3f_pattern_mixture_nc.out.txt: MPlus Syntax 3f output - Pattern mixture model with neighbouring case missing variable restriction;3g_pattern_mixture_ac.inp.txt: MPlus Syntax 3g input - Pattern mixture model with available case missing variable restriction;3g_pattern_mixture_ac.out.txt: MPlus Syntax 3g output - Pattern mixture model with available case missing variable restriction

Staudt, A., & Baumann, S. (2022). Primärdaten zur Studie "Sensitivity analyses for data missing at random versus missing not at random using Latent Growth Modelling: A practical guide for randomised controlled trials" [Files auf CD-ROM].Trier: Psychologisches Datenarchiv PsychData des Leibniz-Institut für Psychologie ZPID.DOI:10.5160/psychdata.stas21pr11

https://doi.org/10.5160/psychdata.stas21pr11

https://hdl.handle.net/20.500.12034/7457

https://doi.org/10.23668/psycharchives.8164

deu

RDC

150

Primärdaten zur Studie "Sensitivity analyses for data missing at random versus missing not at random using Latent Growth Modelling: A practical guide for randomised controlled trials"

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