NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 1 to 15 of 17 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Macho, Siegfried; Ledermann, Thomas – Psychological Methods, 2011
The phantom model approach for estimating, testing, and comparing specific effects within structural equation models (SEMs) is presented. The rationale underlying this novel method consists in representing the specific effect to be assessed as a total effect within a separate latent variable model, the phantom model that is added to the main…
Descriptors: Structural Equation Models, Computation, Comparative Analysis, Sampling
Peer reviewed Peer reviewed
Direct linkDirect link
Vandekerckhove, Joachim; Tuerlinckx, Francis; Lee, Michael D. – Psychological Methods, 2011
Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times--the Wiener diffusion…
Descriptors: Reaction Time, Models, Bayesian Statistics, Experimental Psychology
Peer reviewed Peer reviewed
Direct linkDirect link
Imai, Kosuke; Keele, Luke; Tingley, Dustin – Psychological Methods, 2010
Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…
Descriptors: Structural Equation Models, Statistical Analysis, Statistical Inference, Intervention
Peer reviewed Peer reviewed
Direct linkDirect link
Harder, Valerie S.; Stuart, Elizabeth A.; Anthony, James C. – Psychological Methods, 2010
There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use, and evaluation. In this study, the authors give an overview of available…
Descriptors: Psychological Studies, Probability, Statistical Analysis, Statistical Inference
Peer reviewed Peer reviewed
Direct linkDirect link
Lane, David M.; Sandor, Aniko – Psychological Methods, 2009
Statistical graphs are commonly used in scientific publications. Unfortunately, graphs in psychology journals rarely portray distributional information beyond central tendency, and few graphs portray inferential statistics. Moreover, those that do portray inferential information generally do not portray it in a way that is useful for interpreting…
Descriptors: Graphs, Charts, Design, Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Bonett, Douglas G. – Psychological Methods, 2009
L. Wilkinson and the Task Force on Statistical Inference (1999) recommended reporting confidence intervals for measures of effect sizes. If the sample size is too small, the confidence interval may be too wide to provide meaningful information. Recently, K. Kelley and J. R. Rausch (2006) used an iterative approach to computer-generate tables of…
Descriptors: Intervals, Sample Size, Effect Size, Statistical Inference
Peer reviewed Peer reviewed
Direct linkDirect link
Tonidandel, Scott; LeBreton, James M.; Johnson, Jeff W. – Psychological Methods, 2009
Relative weight analysis is a procedure for estimating the relative importance of correlated predictors in a regression equation. Because the sampling distribution of relative weights is unknown, researchers using relative weight analysis are unable to make judgments regarding the statistical significance of the relative weights. J. W. Johnson…
Descriptors: Multiple Regression Analysis, Statistical Significance, Statistical Inference, Bias
Peer reviewed Peer reviewed
Direct linkDirect link
Maraun, Michael; Gabriel, Stephanie – Psychological Methods, 2010
In his article, "An Alternative to Null-Hypothesis Significance Tests," Killeen (2005) urged the discipline to abandon the practice of "p[subscript obs]"-based null hypothesis testing and to quantify the signal-to-noise characteristics of experimental outcomes with replication probabilities. He described the coefficient that he…
Descriptors: Hypothesis Testing, Statistical Inference, Probability, Statistical Significance
Peer reviewed Peer reviewed
Direct linkDirect link
Killeen, Peter R. – Psychological Methods, 2010
Lecoutre, Lecoutre, and Poitevineau (2010) have provided sophisticated grounding for "p[subscript rep]." Computing it precisely appears, fortunately, no more difficult than doing so approximately. Their analysis will help move predictive inference into the mainstream. Iverson, Wagenmakers, and Lee (2010) have also validated…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Design, Research Methodology
Peer reviewed Peer reviewed
Direct linkDirect link
Lecoutre, Bruno; Lecoutre, Marie-Paule; Poitevineau, Jacques – Psychological Methods, 2010
P. R. Killeen's (2005a) probability of replication ("p[subscript rep]") of an experimental result is the fiducial Bayesian predictive probability of finding a same-sign effect in a replication of an experiment. "p[subscript rep]" is now routinely reported in "Psychological Science" and has also begun to appear in…
Descriptors: Research Methodology, Guidelines, Probability, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Iverson, Geoffrey J.; Wagenmakers, Eric-Jan; Lee, Michael D. – Psychological Methods, 2010
The purpose of the recently proposed "p[subscript rep]" statistic is to estimate the probability of concurrence, that is, the probability that a replicate experiment yields an effect of the same sign (Killeen, 2005a). The influential journal "Psychological Science" endorses "p[subscript rep]" and recommends its use…
Descriptors: Effect Size, Evaluation Methods, Probability, Experiments
Peer reviewed Peer reviewed
Direct linkDirect link
Serlin, Ronald C. – Psychological Methods, 2010
The sense that replicability is an important aspect of empirical science led Killeen (2005a) to define "p[subscript rep]," the probability that a replication will result in an outcome in the same direction as that found in a current experiment. Since then, several authors have praised and criticized 'p[subscript rep]," culminating…
Descriptors: Epistemology, Effect Size, Replication (Evaluation), Measurement Techniques
Peer reviewed Peer reviewed
Direct linkDirect link
Cumming, Geoff – Psychological Methods, 2010
This comment offers three descriptions of "p[subscript rep]" that start with a frequentist account of confidence intervals, draw on R. A. Fisher's fiducial argument, and do not make Bayesian assumptions. Links are described among "p[subscript rep]," "p" values, and the probability a confidence interval will capture…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Methodology, Validity
Peer reviewed Peer reviewed
Direct linkDirect link
Jo, Booil; Asparouhov, Tihomir; Muthen, Bengt O.; Ialongo, Nicholas S.; Brown, C. Hendricks – Psychological Methods, 2008
Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be…
Descriptors: Individual Characteristics, Intervention, Statistical Inference, Inferences
Peer reviewed Peer reviewed
Direct linkDirect link
McGrath, Robert E.; Meyer, Gregory J. – Psychological Methods, 2006
The increased use of effect sizes in single studies and meta-analyses raises new questions about statistical inference. Choice of an effect-size index can have a substantial impact on the interpretation of findings. The authors demonstrate the issue by focusing on two popular effect-size measures, the correlation coefficient and the…
Descriptors: Statistical Inference, Correlation, Effect Size, Measurement Techniques
Previous Page | Next Page ยป
Pages: 1  |  2