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Psychological Methods

Sabrina Thai, Elizabeth Page-Gould
Experience sampling methods allow researchers to examine phenomena in daily life and provide various advantages that complement traditional laboratory methods. However, existing experience sampling methods may be costly, require constant Internet connectivity, may not be designed specifically for experience sampling studies, or require a custom solution from a computer programming consultant. In this article, we present ExperienceSampler, an open-source scaffold for creating experience-sampling smartphone apps designed for Android and iOS devices...
June 15, 2017: Psychological Methods
Jennifer J Pokorny, Alex Norman, Anthony P Zanesco, Susan Bauer-Wu, Baljinder K Sahdra, Clifford D Saron
We present a novel manner in which to visualize the coding of qualitative data that enables representation and analysis of connections between codes using graph theory and network analysis. Network graphs are created from codes applied to a transcript or audio file using the code names and their chronological location. The resulting network is a representation of the coding data that characterizes the interrelations of codes. This approach enables quantification of qualitative codes using network analysis and facilitates examination of associations of network indices with other quantitative variables using common statistical procedures...
June 1, 2017: Psychological Methods
Daniel McNeish
Empirical studies in psychology commonly report Cronbach's alpha as a measure of internal consistency reliability despite the fact that many methodological studies have shown that Cronbach's alpha is riddled with problems stemming from unrealistic assumptions. In many circumstances, violating these assumptions yields estimates of reliability that are too small, making measures look less reliable than they actually are. Although methodological critiques of Cronbach's alpha are being cited with increasing frequency in empirical studies, in this tutorial we discuss how the trend is not necessarily improving methodology used in the literature...
May 29, 2017: Psychological Methods
Craig K Enders, Brian T Keller, Roy Levy
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables, differential relations at Level-1 and Level-2, and incomplete Level-2 variables. Given the limitations of existing imputation tools, the purpose of this manuscript is to describe a flexible imputation approach that can accommodate a diverse set of 2-level analysis problems that includes any of the aforementioned features...
May 29, 2017: 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
Geert H van Kollenburg, Joris Mulder, Jeroen K Vermunt
In order to accurately control the Type I error rate (typically .05), a p value should be uniformly distributed under the null model. The posterior predictive p value (ppp), which is commonly used in Bayesian data analysis, generally does not satisfy this property. For example there have been reports where the sampling distribution of the ppp under the null model was highly concentrated around .50. In this case, a ppp of .20 would indicate model misfit, but when comparing it with a significance level of .05, which is standard statistical practice, the null model would not be rejected...
June 2017: Psychological Methods
Zhao-Hua Lu, Sy-Miin Chow, Eric Loken
We compare the performances of well-known frequentist model fit indices (MFIs) and several Bayesian model selection criteria (MCC) as tools for cross-loading selection in factor analysis under low to moderate sample sizes, cross-loading sizes, and possible violations of distributional assumptions. The Bayesian criteria considered include the Bayes factor (BF), Bayesian Information Criterion (BIC), Deviance Information Criterion (DIC), a Bayesian leave-one-out with Pareto smoothed importance sampling (LOO-PSIS), and a Bayesian variable selection method using the spike-and-slab prior (SSP; Lu, Chow, & Loken, 2016)...
June 2017: Psychological Methods
Minjeong Jeon, Paul De Boeck
The purpose of this article is to investigate the decision qualities of the Bayes factor (BF) method compared with the p value-based null hypothesis significance testing (NHST). The performance of the 2 methods is assessed in terms of the false- and true-positive rates, as well as the false-discovery rates and the posterior probabilities of the null hypothesis for 2 different models: an independent-samples t test and an analysis of variance (ANOVA) model with 2 random factors. Our simulation study results showed the following: (a) The common BF > 3 criterion is more conservative than the NHST α = ...
June 2017: Psychological Methods
Joseph W Houpt, Andrew Heathcote, Ami Eidels
The question of cognitive architecture-how cognitive processes are temporally organized-has arisen in many areas of psychology. This question has proved difficult to answer, with many proposed solutions turning out to be spurious. Systems factorial technology (Townsend & Nozawa, 1995) provided the first rigorous empirical and analytical method of identifying cognitive architecture, using the survivor interaction contrast (SIC) to determine when people are using multiple sources of information in parallel or in series...
June 2017: Psychological Methods
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