| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A mixed-effects location scale model for time-to-event data: A smoking behavior application
|
Courvoisier, Delphine
|
|
2019
|
94 |
C |
p. 42-49
|
artikel
|
| 2 |
A review of EMA assessment period reporting for mood variables in substance use research: Expanding existing EMA guidelines
|
Singh, Narayan B.
|
|
2019
|
94 |
C |
p. 133-146
|
artikel
|
| 3 |
A robust alternative estimator for small to moderate sample SEM: Bias-corrected factor score path analysis
|
Kelcey, Ben
|
|
2019
|
94 |
C |
p. 83-98
|
artikel
|
| 4 |
A straightforward approach for coping with unreliability of person means when parsing within-person and between-person effects in longitudinal studies
|
Gottfredson, Nisha C.
|
|
2019
|
94 |
C |
p. 156-161
|
artikel
|
| 5 |
A tutorial on individual participant data meta-analysis using Bayesian multilevel modeling to estimate alcohol intervention effects across heterogeneous studies
|
Huh, David
|
|
2019
|
94 |
C |
p. 162-170
|
artikel
|
| 6 |
Beyond path diagrams: Enhancing applied structural equation modeling research through data visualization
|
Hallgren, Kevin A.
|
|
2019
|
94 |
C |
p. 74-82
|
artikel
|
| 7 |
Conducting sensitivity analyses to identify and buffer power vulnerabilities in studies examining substance use over time
|
Lane, Sean P.
|
|
2019
|
94 |
C |
p. 117-123
|
artikel
|
| 8 |
Developmental considerations in survival models as applied to substance use research
|
Jackson, Kristina M.
|
|
2019
|
94 |
C |
p. 36-41
|
artikel
|
| 9 |
Editorial Board
|
|
|
2019
|
94 |
C |
p. ii
|
artikel
|
| 10 |
How to implement directed acyclic graphs to reduce bias in addiction research
|
Wouk, Kathryn
|
|
2019
|
94 |
C |
p. 109-116
|
artikel
|
| 11 |
Implementing statistical methods for generalizing randomized trial findings to a target population
|
Ackerman, Benjamin
|
|
2019
|
94 |
C |
p. 124-132
|
artikel
|
| 12 |
Improving the implementation of quantitative methods in addiction research: Introduction to the special issue
|
King, Kevin M.
|
|
2019
|
94 |
C |
p. 1-3
|
artikel
|
| 13 |
Interaction effects may actually be nonlinear effects in disguise: A review of the problem and potential solutions
|
Belzak, William C.M.
|
|
2019
|
94 |
C |
p. 99-108
|
artikel
|
| 14 |
Mediation analysis with binary outcomes: Direct and indirect effects of pro-alcohol influences on alcohol use disorders
|
Feingold, Alan
|
|
2019
|
94 |
C |
p. 26-35
|
artikel
|
| 15 |
Mediation analysis with zero-inflated substance use outcomes: Challenges and recommendations
|
O'Rourke, Holly P.
|
|
2019
|
94 |
C |
p. 16-25
|
artikel
|
| 16 |
Modeling change trajectories with count and zero-inflated outcomes: Challenges and recommendations
|
Grimm, Kevin J.
|
|
2019
|
94 |
C |
p. 4-15
|
artikel
|
| 17 |
Quantifying the impact of partial measurement invariance in diagnostic research: An application to addiction research
|
Lai, Mark H.C.
|
|
2019
|
94 |
C |
p. 50-56
|
artikel
|
| 18 |
Simplifying the implementation of modern scale scoring methods with an automated R package: Automated moderated nonlinear factor analysis (aMNLFA)
|
Gottfredson, Nisha C.
|
|
2019
|
94 |
C |
p. 65-73
|
artikel
|
| 19 |
Statistical methods for evaluating the correlation between timeline follow-back data and daily process data with applications to research on alcohol and marijuana use
|
Liu, Wanjun
|
|
2019
|
94 |
C |
p. 147-155
|
artikel
|
| 20 |
Toward more efficient diagnostic criteria sets and rules: The use of optimization approaches in addiction science
|
Stevens, Jordan E.
|
|
2019
|
94 |
C |
p. 57-64
|
artikel
|
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