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Psychological Methods

Gwowen Shieh
Moderation analysis is a vital aspect of research in education, management, psychology, and related disciplines. Although several methodological artifacts have been identified and examined, heterogeneity of variance remains one of the unique and problematic factors known as detrimental to statistical power in the detection of moderating effects. To alleviate the difficulty in assessing moderation because of low statistical power, this article describes feasible solutions to sample size calculations for tests of hypothesized interactions between categorical variables under variance heterogeneity...
May 11, 2017: Psychological Methods
Rolf Ulrich, Jeff Miller
p-curves provide a useful window for peeking into the file drawer in a way that might reveal p-hacking (Simonsohn, Nelson, & Simmons, 2014a). The properties of p-curves are commonly investigated by computer simulations. On the basis of these simulations, it has been proposed that the skewness of this curve can be used as a diagnostic tool to decide whether the significant p values within a certain domain of research suggest the presence of p-hacking or actually demonstrate that there is a true effect. Here we introduce a rigorous mathematical approach that allows the properties of p-curves to be examined without simulations...
April 20, 2017: Psychological Methods
Taehun Lee, Robert C MacCallum, Michael W Browne
Extending work by Waller (2008) on fungible regression coefficients, we propose a method for computation of fungible parameter estimates in structural equation modeling. Such estimates are defined as distinct alternative solutions for parameter estimates, where all fungible solutions yield identical model fit that is only slightly worse than the fit provided by optimal estimates. When such alternative estimates are found to be highly discrepant from optimal estimates, then substantive interpretation based on optimal estimates is called into question...
April 17, 2017: Psychological Methods
Brandon J George, Peng Li, Harris R Lieberman, Greg Pavela, Andrew W Brown, Kevin R Fontaine, Madeline M Jeansonne, Gareth R Dutton, Adeniyi J Idigo, Mariel A Parman, Donald B Rubin, David B Allison
Blinded randomized controlled trials (RCT) require participants to be uncertain if they are receiving a treatment or placebo. Although uncertainty is ideal for isolating the treatment effect from all other potential effects, it is poorly suited for estimating the treatment effect under actual conditions of intended use-when individuals are certain that they are receiving a treatment. We propose an experimental design, randomization to randomization probabilities (R2R), which significantly improves estimates of treatment effects under actual conditions of use by manipulating participant expectations about receiving treatment...
April 13, 2017: Psychological Methods
Prathiba Natesan, Larry V Hedges
Although immediacy is one of the necessary criteria to show strong evidence of a causal relation in single case designs (SCDs), no inferential statistical tool is currently used to demonstrate it. We propose a Bayesian unknown change-point model to investigate and quantify immediacy in SCD analysis. Unlike visual analysis that considers only 3-5 observations in consecutive phases to investigate immediacy, this model considers all data points. Immediacy is indicated when the posterior distribution of the unknown change-point is narrow around the true value of the change-point...
April 13, 2017: Psychological Methods
Inbal Nahum-Shani, John J Dziak, Linda M Collins
Factorial experimental designs have many applications in the behavioral sciences. In the context of intervention development, factorial experiments play a critical role in building and optimizing high-quality, multicomponent behavioral interventions. One challenge in implementing factorial experiments in the behavioral sciences is that individuals are often clustered in social or administrative units and may be more similar to each other than to individuals in other clusters. This means that data are dependent within clusters...
April 6, 2017: Psychological Methods
W Alan Nicewander
The most widely used, general index of measurement precision for psychological and educational test scores is the reliability coefficient-a ratio of true variance for a test score to the true-plus-error variance of the score. In item response theory (IRT) models for test scores, the information function is the central, conditional index of measurement precision. In this inquiry, conditional reliability coefficients for a variety of score types are derived as simple transformations of information functions. It is shown, for example, that the conditional reliability coefficient for an ordinary, number-correct score, X, is equal to, ρ(X,X'|θ)=I(X,θ)/[I(X,θ)+1] Where: θ is a latent variable measured by an observed test score, X; p(X, X'|θ) is the conditional reliability of X at a fixed value of θ; and I(X, θ) is the score information function...
April 6, 2017: Psychological Methods
Ken Kelley, Francis Bilson Darku, Bhargab Chattopadhyay
Sequential estimation is a well recognized approach to inference in statistical theory. In sequential estimation the sample size to use is not specified at the start of the study, and instead study outcomes are used to evaluate a predefined stopping rule, if sampling should continue or stop. In this article we develop a general theory for sequential estimation procedure for constructing a narrow confidence interval for a general class of effect sizes with a specified level of confidence (e.g., 95%) and a specified upper bound on the confidence interval width...
April 6, 2017: Psychological Methods
Herbert Hoijtink, Rens van de Schoot
Muthén and Asparouhov (2012) propose to evaluate model fit in structural equation models based on approximate (using small variance priors) instead of exact equality of (combinations of) parameters to zero. This is an important development that adequately addresses Cohen's (1994) The Earth is Round (p < .05), which stresses that point null-hypotheses are so precise that small and irrelevant differences from the null-hypothesis may lead to their rejection. It is tempting to evaluate small variance priors using readily available approaches like the posterior predictive p value and the DIC...
April 3, 2017: Psychological Methods
Michael C Edwards, Carrie R Houts, Li Cai
Item response theory (IRT) is a widely used measurement model. When considering its use in education, health outcomes, and psychology, it is likely to be one of the most impactful psychometric models in existence. IRT has many advantages over classical test theory-based measurement models. For these advantages to hold in practice, strong assumptions must be satisfied. One of these assumptions, local independence, is the focus of the work described here. Local independence is the assumption that, conditional on the latent variable(s), item responses are unrelated to one another (i...
April 3, 2017: Psychological Methods
Maria Bolsinova, Herbert Hoijtink, Jorine Adinda Vermeulen, Anton Béguin
Linking and equating procedures are used to make the results of different test forms comparable. In the cases where no assumption of random equivalent groups can be made some form of linking design is used. In practice the amount of data available to link the two tests is often very limited due to logistic and security reasons, which affects the precision of linking procedures. This study proposes to enhance the quality of linking procedures based on sparse data by using Bayesian methods which combine the information in the linking data with background information captured in informative prior distributions...
April 3, 2017: Psychological Methods
Mariola Moeyaert, David Rindskopf, Patrick Onghena, Wim Van den Noortgate
The focus of this article is to describe Bayesian estimation, including construction of prior distributions, and to compare parameter recovery under the Bayesian framework (using weakly informative priors) and the maximum likelihood (ML) framework in the context of multilevel modeling of single-case experimental data. Bayesian estimation results were found similar to ML estimation results in terms of the treatment effect estimates, regardless of the functional form and degree of information included in the prior specification in the Bayesian framework...
March 30, 2017: Psychological Methods
Mark H C Lai, Oi-Man Kwok, Yu-Yu Hsiao, Qian Cao
The research literature has paid little attention to the issue of finite population at a higher level in hierarchical linear modeling. In this article, we propose a method to obtain finite-population-adjusted standard errors of Level-1 and Level-2 fixed effects in 2-level hierarchical linear models. When the finite population at Level-2 is incorrectly assumed as being infinite, the standard errors of the fixed effects are overestimated, resulting in lower statistical power and wider confidence intervals. The impact of ignoring finite population correction is illustrated by using both a real data example and a simulation study with a random intercept model and a random slope model...
March 16, 2017: Psychological Methods
Morten Moshagen, Max Auerswald
Guidelines to evaluate the fit of structural equation models can only offer meaningful insights to the extent that they apply equally to a wide range of situations. However, a number of previous studies found that statistical power to reject a misspecified model increases and descriptive fit-indices deteriorate when loadings are high, thereby inappropriately panelizing high reliability indicators. Based on both theoretical considerations and empirical simulation studies, we show that previous results only hold for a particular definition and a particular type of model error...
March 16, 2017: Psychological Methods
Rumen Manolov, Patrick Onghena
Alternating treatments designs (ATDs) have received comparatively less attention than other single-case experimental designs in terms of data analysis, as most analytical proposals and illustrations have been made in the context of designs including phases with several consecutive measurements in the same condition. One of the specific features of ATDs is the rapid (and usually randomly determined) alternation of conditions, which requires adapting the analytical techniques. First, we review the methodologically desirable features of ATDs, as well as the characteristics of the published single-case research using an ATD, which are relevant for data analysis...
March 16, 2017: Psychological Methods
Jason D Rights, Sonya K Sterba
Psychologists commonly apply regression mixture models in single-level (i.e., unclustered) and multilevel (i.e., clustered) data analysis contexts. Though researchers applying nonmixture regression models typically report R-squared measures of explained variance, there has been no general treatment of R-squared measures for single-level and multilevel regression mixtures. Consequently, it is common for researchers to summarize results of a fitted regression mixture by simply reporting class-specific regression coefficients and their associated p values, rather than considering measures of effect size...
March 16, 2017: Psychological Methods
Yang Tang, Thomas D Cook, Yasemin Kisbu-Sakarya
In the "sharp" regression discontinuity design (RD), all units scoring on one side of a designated score on an assignment variable receive treatment, whereas those scoring on the other side become controls. Thus the continuous assignment variable and binary treatment indicator are measured on the same scale. Because each must be in the impact model, the resulting multi-collinearity reduces the efficiency of the RD design. However, untreated comparison data can be added along the assignment variable, and a comparative regression discontinuity design (CRD) is then created...
March 16, 2017: Psychological Methods
Jolynn Pek, David B Flora
Statistical practice in psychological science is undergoing reform which is reflected in part by strong recommendations for reporting and interpreting effect sizes and their confidence intervals. We present principles and recommendations for research reporting and emphasize the variety of ways effect sizes can be reported. Additionally, we emphasize interpreting and reporting unstandardized effect sizes because of common misconceptions regarding standardized effect sizes which we elucidate. Effect sizes should directly answer their motivating research questions, be comprehensible to the average reader, and be based on meaningful metrics of their constituent variables...
March 9, 2017: Psychological Methods
Larry V Hedges
I discuss how methods that adjust for publication selection involve implicit or explicit selection models. Such models describe the relation between the studies conducted and those actually observed. I argue that the evaluation of selection models should include an evaluation of the plausibility of the empirical implications of that model. This includes how many studies would have had to exist to yield the observed sample of studies. I also argue that the amount of influence that one or a small number of studies might have on the overall results is also important to understand...
March 2017: Psychological Methods
Martyna Citkowicz, Jack L Vevea
Quantitative research literature is often biased because studies that fail to find a significant effect (or that demonstrate effects in an undesired or unexpected direction) are less likely to be published. This phenomenon, termed publication bias, can cause problems when researchers attempt to synthesize results using meta-analytic methods. Various techniques exist that attempt to estimate and correct meta-analyses for publication bias. However, there is no single method that can (a) account for continuous moderators by including them within the model, (b) allow for substantial data heterogeneity, (c) produce an adjusted mean effect size, (d) include a formal test for publication bias, and (e) allow for correction when only a small number of effects is included in the analysis...
March 2017: Psychological Methods
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