journal
https://read.qxmd.com/read/38753382/estimation-of-planned-and-unplanned-missing-individual-scores-in-longitudinal-designs-using-continuous-time-state-space-models
#1
JOURNAL ARTICLE
José Ángel Martínez-Huertas, Eduardo Estrada, Ricardo Olmos
Latent change score (LCS) models within a continuous-time state-space modeling framework provide a convenient statistical approach for analyzing developmental data. In this study, we evaluate the robustness of such an approach in the context of accelerated longitudinal designs (ALDs). ALDs are especially interesting because they imply a very high rate of planned data missingness. Additionally, most longitudinal studies present unexpected participant attrition leading to unplanned missing data. Therefore, in ALDs, both sources of data missingness are combined...
May 16, 2024: Psychological Methods
https://read.qxmd.com/read/38709627/are-factor-scores-measurement-invariant
#2
JOURNAL ARTICLE
Mark H C Lai, Winnie W-Y Tse
There has been increased interest in practical methods for integrative analysis of data from multiple studies or samples, and using factor scores to represent constructs has become a popular and practical alternative to latent variable models with all individual items. Although researchers are aware that scores representing the same construct should be on a similar metric across samples-namely they should be measurement invariant-for integrative data analysis, the methodological literature is unclear whether factor scores would satisfy such a requirement...
May 6, 2024: Psychological Methods
https://read.qxmd.com/read/38709626/a-deep-learning-method-for-comparing-bayesian-hierarchical-models
#3
JOURNAL ARTICLE
Lasse Elsemüller, Martin Schnuerch, Paul-Christian Bürkner, Stefan T Radev
Bayesian model comparison (BMC) offers a principled approach to assessing the relative merits of competing computational models and propagating uncertainty into model selection decisions. However, BMC is often intractable for the popular class of hierarchical models due to their high-dimensional nested parameter structure. To address this intractability, we propose a deep learning method for performing BMC on any set of hierarchical models which can be instantiated as probabilistic programs. Since our method enables amortized inference, it allows efficient re-estimation of posterior model probabilities and fast performance validation prior to any real-data application...
May 6, 2024: Psychological Methods
https://read.qxmd.com/read/38647485/combinational-regularity-analysis-cora-an-introduction-for-psychologists
#4
JOURNAL ARTICLE
Alrik Thiem, Lusine Mkrtchyan, Zuzana Sebechlebská
Increasingly, psychologists make use of modern configurational comparative methods (CCMs), such as qualitative comparative analysis (QCA) and coincidence analysis (CNA), to infer regularity-theoretic causal structures from psychological data. At the same time, existing CCMs remain unable to reveal such structures in the presence of complex effects. Given the strong emphasis configurational methodology generally puts on the notion of complex causation, and the ubiquity of multieffect problems in psychological research, such as multimorbidity and polypharmacy, this limitation is severe...
April 22, 2024: Psychological Methods
https://read.qxmd.com/read/38647484/the-plausibility-of-alternative-data-generating-mechanisms-comment-on-and-attempt-at-replication-of-dishop-2022
#5
JOURNAL ARTICLE
Jonas W B Lang, Paul D Bliese
Dishop (see record 2022-78260-001) identifies the consensus emergence model (CEM) as a useful tool for future research on emergence but argues that autoregressive models with positive autoregressive effects are an important alternative data-generating mechanism that researchers need to rule out. Here, we acknowledge that alternative data-generating mechanisms are possibility for most, if not all, nonexperimental designs and appreciate Dishop's attempts to identify cases where the CEM could provide misleading results...
April 22, 2024: Psychological Methods
https://read.qxmd.com/read/38647483/causal-relationships-in-longitudinal-observational-data-an-integrative-modeling-approach
#6
JOURNAL ARTICLE
Claudinei E Biazoli, João R Sato, Michael Pluess
Much research in psychology relies on data from observational studies that traditionally do not allow for causal interpretation. However, a range of approaches in statistics and computational sciences have been developed to infer causality from correlational data. Based on conceptual and theoretical considerations on the integration of interventional and time-restrainment notions of causality, we set out to design and empirically test a new approach to identify potential causal factors in longitudinal correlational data...
April 22, 2024: Psychological Methods
https://read.qxmd.com/read/38602781/testing-similarity-in-longitudinal-networks-the-individual-network-invariance-test
#7
JOURNAL ARTICLE
Ria H A Hoekstra, Sacha Epskamp, Andrew A Nierenberg, Denny Borsboom, Richard J McNally
The comparison of idiographic network structures to determine the presence of heterogeneity is a challenging endeavor in many applied settings. Previously, researchers eyeballed idiographic networks, computed correlations, and used techniques that make use of the multilevel structure of the data (e.g., group iterative multiple model estimation and multilevel vector autoregressive) to investigate individual differences. However, these methods do not allow for testing the (in)equality of idiographic network structures directly...
April 11, 2024: Psychological Methods
https://read.qxmd.com/read/38573668/generalized-gaussian-signal-detection-theory-a-unified-signal-detection-framework-for-confidence-data-analysis
#8
JOURNAL ARTICLE
Kiyofumi Miyoshi, Shin'ya Nishida
Human decision behavior entails a graded awareness of its certainty, known as a feeling of confidence. Until now, considerable interest has been paid to behavioral and computational dissociations of decision and confidence, which has raised an urgent need for measurement frameworks that can quantify the efficiency of confidence rating relative to decision accuracy (metacognitive efficiency). As a unique addition to such frameworks, we have developed a new signal detection theory paradigm utilizing the generalized Gaussian distribution (GGSDT)...
April 4, 2024: Psychological Methods
https://read.qxmd.com/read/38573667/normality-assumption-in-latent-interaction-models
#9
JOURNAL ARTICLE
Sirio Lonati, Mikko Rönkkö, John Antonakis
Latent moderated structural equation (LMS) is one of the most common techniques for estimating interaction effects involving latent variables (i.e., XWITH command in Mplus). However, empirical applications of LMS often overlook that this estimation technique assumes normally distributed variables and that violations of this assumption may lead to seriously biased parameter estimates. Against this backdrop, we study the robustness of LMS to different shapes and sources of nonnormality and examine whether various statistical tests can help researchers detect such distributional misspecifications...
April 4, 2024: Psychological Methods
https://read.qxmd.com/read/38573666/the-pairwise-approximate-spatiotemporal-symmetry-algorithm-a-method-for-segmenting-time-series-pairs
#10
JOURNAL ARTICLE
Gustav R Sjobeck, Steven M Boker, Carl E Scheidt, Wolfgang Tschacher
Methods that measure the association between two intensively measured time series are of interest to researchers studying the symmetry of behaviors during social interaction. Such methods have historically focused on aggregating the amount of symmetry across all measurement occasions. However, it is rarely expected that symmetry is present at all measurement occasions. The current method, the pairwise approximate spatiotemporal symmetry (PASS) algorithm, is an approach that may be used to determine which measurement occasions in pairwise time series are indicative of symmetry and which are not...
April 4, 2024: Psychological Methods
https://read.qxmd.com/read/38573665/correcting-for-collider-effects-and-sample-selection-bias-in-psychological-research
#11
JOURNAL ARTICLE
Sophia J Lamp, David P MacKinnon
Colliders, variables that serve as a common outcome of an independent and dependent variable, pose a major challenge in psychological research. Collider variables can induce bias in the estimation of a population relationship of interest when (a) the composition of a research sample is restricted by scores on a collider variable or (b) researchers adjust for a collider variable in their statistical analyses, as they might do for confounder variables. Both cases interfere with the accuracy and generalizability of statistical results...
April 4, 2024: Psychological Methods
https://read.qxmd.com/read/38573664/will-all-youth-answer-sexual-orientation-and-gender-related-survey-questions-an-analysis-of-missingness-in-a-large-u-s-survey-of-adolescents-and-young-adults
#12
JOURNAL ARTICLE
Sabra L Katz-Wise, Lynsie R Ranker, R Korkodilos, Jennifer Conti, Kimberly M Nelson, Ziming Xuan, Allegra R Gordon
Some researchers and clinicians may feel hesitant to assess sexual orientation and gender-related characteristics in youth surveys because they are unsure if youth will respond to these questions or are concerned the questions will cause discomfort or offense. This can result in missed opportunities to identify LGBTQ+ youth and address health inequities among this population. The aim of this study was to examine the prevalence and sociodemographic patterns of missingness among survey questions assessing current sexual orientation, gender identity and expression (SOGIE), and past change in sexual orientation (sexual fluidity) among a diverse sample of U...
April 4, 2024: Psychological Methods
https://read.qxmd.com/read/38573663/relating-violations-of-measurement-invariance-to-group-differences-in-response-times
#13
JOURNAL ARTICLE
Dylan Molenaar, Remco Feskens
Measurement invariance is an assumption underlying the regression of a latent variable on a background variable. It requires the measurement model parameters of the latent variable to be equal across the levels of the background variable. Item-specific violations of this assumption are referred to as differential item functioning and are ideally substantively explainable to warrant theoretically valid and meaningful results. Past research has focused on developing statistical approaches to explain differential item functioning effects in terms of item- or person-specific covariates...
April 4, 2024: Psychological Methods
https://read.qxmd.com/read/38512203/the-bayes-factor-hdi-rope-and-frequentist-equivalence-tests-can-all-be-reverse-engineered-almost-exactly-from-one-another-reply-to-linde-et-al-2021
#14
JOURNAL ARTICLE
Harlan Campbell, Paul Gustafson
Following an extensive simulation study comparing the operating characteristics of three different procedures used for establishing equivalence (the frequentist "TOST," the Bayesian "HDI-ROPE," and the Bayes factor interval null procedure), Linde et al. (2021) conclude with the recommendation that "researchers rely more on the Bayes factor interval null approach for quantifying evidence for equivalence" (p. 1). We redo the simulation study of Linde et al. (2021) in its entirety but with the different procedures calibrated to have the same predetermined maximum Type I error rate...
March 21, 2024: Psychological Methods
https://read.qxmd.com/read/38483524/beta-binomial-meta-analysis-of-individual-differences-based-on-sample-means-and-standard-deviations-studying-reliability-of-sum-scores-of-binary-items
#15
JOURNAL ARTICLE
Philipp Doebler, Susanne Frick, Anna Doebler
Individual differences are studied with a multitude of test instruments. Meta-analysis of tests is useful to understand whether individual differences in certain populations can be detected with the help of a class of tests. A method for the quantitative meta-analytical evaluation of test instruments with dichotomous items is introduced. The method assumes beta-binomially distributed test scores, an assumption that has been demonstrated to be plausible in many settings. With this assumption, the method only requires sample means and standard deviations of sum scores (or equivalently means and standard deviations of percent-correct scores), in contrast to methods that use estimates of reliability for a similar purpose...
March 14, 2024: Psychological Methods
https://read.qxmd.com/read/38421769/the-monotonic-linear-model-testing-for-removable-interactions
#16
JOURNAL ARTICLE
John C Dunn, Laura M Anderson
Loftus (1978) highlighted the distinction between a theoretical concept such as memory or attention, and its observed measure such as hit rate or percent correct. If the functional relationship between the concept and its measure is nonlinear then only some interaction effects are interpretable. This is an example of the wider "problem of coordination" which pervades scientific measurement. Loftus drew on the principles of additive conjoint measurement (ACM) to discuss the consequences when the coordination function is assumed to be monotonic...
February 29, 2024: Psychological Methods
https://read.qxmd.com/read/38421768/a-screen-time-based-mixture-model-for-identifying-and-monitoring-careless-and-insufficient-effort-responding-in-ecological-momentary-assessment-data
#17
JOURNAL ARTICLE
Esther Ulitzsch, Steffen Nestler, Oliver Lüdtke, Gabriel Nagy
Ecological momentary assessment (EMA) involves repeated real-time sampling of respondents' current behaviors and experiences. The intensive repeated assessment imposes an increased burden on respondents, rendering EMAs vulnerable to respondent noncompliance and/or careless and insufficient effort responding (C/IER). We developed a mixture modeling approach that equips researchers with a tool for (a) gauging the degree of C/IER contamination of their EMA data and (b) studying the trajectory of C/IER across the study...
February 29, 2024: Psychological Methods
https://read.qxmd.com/read/38358680/estimating-curvilinear-time-varying-treatment-effects-combining-g-estimation-of-structural-nested-mean-models-with-time-varying-effect-models-for-longitudinal-causal-inference
#18
JOURNAL ARTICLE
Wen Wei Loh
Longitudinal designs can fortify causal inquiries of a focal predictor (i.e., treatment) on an outcome. But valid causal inferences are complicated by causal feedback between confounders and treatment over time. G-estimation of a structural nested mean model (SNMM) is designed to handle the complexities beset by measured time-varying or treatment-dependent confounding in longitudinal data. But valid inference requires correctly specifying the functional form of the SNMM, such as how the effects stay constant or change over time...
February 15, 2024: Psychological Methods
https://read.qxmd.com/read/38358679/linear-mixed-models-and-latent-growth-curve-models-for-group-comparison-studies-contaminated-by-outliers
#19
JOURNAL ARTICLE
Fabio Mason, Eva Cantoni, Paolo Ghisletta
The linear mixed model (LMM) and latent growth model (LGM) are frequently applied to within-subject two-group comparison studies to investigate group differences in the time effect, supposedly due to differential group treatments. Yet, research about LMM and LGM in the presence of outliers (defined as observations with a very low probability of occurrence if assumed from a given distribution) is scarce. Moreover, when such research exists, it focuses on estimation properties (bias and efficiency), neglecting inferential characteristics (e...
February 15, 2024: Psychological Methods
https://read.qxmd.com/read/38330342/individual-level-probabilities-and-cluster-level-proportions-toward-interpretable-level-2-estimates-in-unconflated-multilevel-models-for-binary-outcomes
#20
JOURNAL ARTICLE
Timothy Hayes
Multilevel models allow researchers to test hypotheses at multiple levels of analysis-for example, assessing the effects of both individual-level and school-level predictors on a target outcome. To assess these effects with the greatest clarity, researchers are well-advised to cluster mean center all Level 1 predictors and explicitly incorporate the cluster means into the model at Level 2. When an outcome of interest is continuous, this unconflated model specification serves both to increase model accuracy, by separating the level-specific effects of each predictor, and to increase model interpretability, by reframing the random intercepts as unadjusted cluster means...
February 8, 2024: Psychological Methods
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