[HTML][HTML] Description, prediction and causation: Methodological challenges of studying child and adolescent development

EL Hamaker, JD Mulder, MH van IJzendoorn - Developmental cognitive …, 2020 - Elsevier
Scientific research can be categorized into: a) descriptive research, with the main goal to
summarize characteristics of a group (or person); b) predictive research, with the main goal …

Common methodological mistakes

JN Wulff, GB Sajons, G Pogrebna, S Lonati… - The Leadership …, 2023 - Elsevier
For scientific discoveries to be valid—whether in theory or empirically—a phenomenon must
be accurately described: The scientist must use appropriate counterfactuals and eliminate …

Beyond experiments

E Diener, R Northcott, MJ Zyphur… - Perspectives on …, 2022 - journals.sagepub.com
It is often claimed that only experiments can support strong causal inferences and therefore
they should be privileged in the behavioral sciences. We disagree. Overvaluing experiments …

Characteristics, consent patterns, and challenges of randomized trials using the Trials within Cohorts (TwiCs) design a sco** review

A Amstutz, CM Schönenberger, B Speich… - Journal of Clinical …, 2024 - Elsevier
Abstract Objective Trials within Cohorts (TwiCs) is a pragmatic design approach that may
overcome frequent challenges of traditional randomized trials such as slow recruitment …

[KNIHA][B] Quasi-experimentation: A guide to design and analysis

CS Reichardt - 2019 - books.google.com
Featuring engaging examples from diverse disciplines, this book explains how to use
modern approaches to quasi-experimentation to derive credible estimates of treatment …

Causal inference and generalization in field settings: Experimental and quasi-experimental designs.

SG West, JC Biesanz, SC Pitts - 2000 - psycnet.apa.org
This chapter introduces researchers in social psychology to designs that permit relatively
strong causal inferences in the field. Considered are some basic issues in inferring …

Confounding in statistical mediation analysis: What it is and how to address it.

MJ Valente, WE Pelham III, H Smyth… - Journal of counseling …, 2017 - psycnet.apa.org
Psychology researchers are often interested in mechanisms underlying how randomized
interventions affect outcomes such as substance use and mental health. Mediation analysis …

Propensity scores as a basis for equating groups: basic principles and application in clinical treatment outcome research.

SG West, H Cham, F Thoemmes… - Journal of consulting …, 2014 - psycnet.apa.org
A propensity score is the probability that a participant is assigned to the treatment group
based on a set of baseline covariates. Propensity scores provide an excellent basis for …

Propensity score analysis with missing data.

H Cham, SG West - Psychological methods, 2016 - psycnet.apa.org
Propensity score analysis is a method that equates treatment and control groups on a
comprehensive set of measured confounders in observational (nonrandomized) studies. A …

The potential of relevance interventions for scaling up: A cluster-randomized trial testing the effectiveness of a relevance intervention in math classrooms.

H Gaspard, C Parrisius, H Piesch… - Journal of …, 2021 - psycnet.apa.org
Relevance interventions have shown a great potential to foster motivation and achievement
(Lazowski & Hulleman, 2016). Yet, further research is warranted to test how such …