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[HTML][HTML] Description, prediction and causation: Methodological challenges of studying child and adolescent development
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 …
summarize characteristics of a group (or person); b) predictive research, with the main goal …
Common methodological mistakes
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 …
be accurately described: The scientist must use appropriate counterfactuals and eliminate …
Beyond experiments
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 …
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
Abstract Objective Trials within Cohorts (TwiCs) is a pragmatic design approach that may
overcome frequent challenges of traditional randomized trials such as slow recruitment …
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 …
modern approaches to quasi-experimentation to derive credible estimates of treatment …
Causal inference and generalization in field settings: Experimental and quasi-experimental designs.
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 …
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.
Psychology researchers are often interested in mechanisms underlying how randomized
interventions affect outcomes such as substance use and mental health. Mediation analysis …
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.
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 …
based on a set of baseline covariates. Propensity scores provide an excellent basis for …
Propensity score analysis with missing data.
Propensity score analysis is a method that equates treatment and control groups on a
comprehensive set of measured confounders in observational (nonrandomized) studies. 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.
Relevance interventions have shown a great potential to foster motivation and achievement
(Lazowski & Hulleman, 2016). Yet, further research is warranted to test how such …
(Lazowski & Hulleman, 2016). Yet, further research is warranted to test how such …