Factor Model Comparisons with Conditioning Information

2021 ◽  
Author(s):  
Junbo L. Wang ◽  
Wayne Ferson ◽  
Andrew F. Siegel
Keyword(s):  
Factor Model ◽  
Model Comparisons ◽  
Conditioning Information

scholarly journals Bayes Factor Model Comparisons Across Parameter Values for Mixed Models

2021 ◽  
Author(s):  
Maximilian Linde ◽  
Don van Ravenzwaaij
Keyword(s):  
Repeated Measures ◽  
Model Comparison ◽  
Bayes Factor ◽  
Factor Model ◽  
Simulated Data ◽  
Experimental Manipulation ◽  
Data Set ◽  
Model Comparisons ◽  
Multiple Data ◽  
Multiple Data Sets

Nested data structures, in which conditions include multiple trials, are often analyzed using repeated-measures analysis of variance or mixed effects models. Typically, researchers are interested in determining whether there is an effect of the experimental manipulation. Unfortunately, these kinds of analyses have different appropriate specifications for the null and alternative models, and a discussion on which is to be preferred and when is sorely lacking. van Doorn et al. (2021) performed three types of Bayes factor model comparisons on a simulated data set in order to examine which model comparison is most suitable for quantifying evidence for or against the presence of an effect of the experimental manipulation. Here we extend their results by simulating multiple data sets for various scenarios and by using different prior specifications. We demonstrate how three different Bayes factor model comparison types behave under changes in different parameters, and we make concrete recommendations on which model comparison is most appropriate for different scenarios.

scholarly journals The Life Orientation Test: A Confirmatory Factor Analysis Across Three Age Groups

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 459-459
Author(s):  
Robert Intrieri ◽  
Paige Goodwin
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Model ◽  
Age Groups ◽  
Well Being ◽  
Model Comparisons ◽  
Life Orientation Test ◽  
Life Orientation ◽  
Confirmatory Factor ◽  
Orientation Test

Abstract The Life Orientation Test (LOT; Scheier & Carver, 1985) was developed as a measure of dispositional optimism. Optimism has been linked to positive life outcomes and is associated with psychological (Carver & Gaines, 1987; Scheier & Carver, 1985) and physical (Scheier & Carver, 1987; Scheier et al. 1989) well-being. The current study assessed 520 people placed into three age groups: young adult (n =149), middle-age adult (n = 252), and older adult (n = 119). The mean age for the young group was 19.24 (SD = 2.01), middle-aged (47.68 (SD = 4.75), and old was 71.99 (SD = 7.21). Data were submitted for a confirmatory factor analysis (CFA) which tested for invariance across the age groups. Previous factor analyses have identified two distinct factors representing optimism and pessimism. Results from the CFA showed that both Configural and Metric invariance models demonstrated acceptable fit for the two factor model (□2(df=57) = 61.92, p = 0.3047; □2(df=69) = 78.77, p = 0.1974). In contrast, Scalar invariance resulted in a poor fit across the three age groups (□2(df=81) = 139.288, p < 0.0001). Model comparisons revealed no significant differences between Configural and Metric models (□2(df=12) = 16.996, p = 0.1498). Model comparisons between Configural and Scalar and Metric and Scalar were (□2(df=24) = 78.947, p < 0.0001; □2(df=12) = 61.764, p < 0.0001). These results confirm previous research that shows a correlated two factor model consistent with the concept that optimism and pessimism are correlated elements rather than two ends of a continuum.

scholarly journals Principles of Model Specification in ANOVA Designs

2021 ◽  
Author(s):  
Jeffrey Rouder ◽  
Martin Schnuerch ◽  
Julia M. Haaf ◽  
Richard Donald Morey
Keyword(s):  
Experimental Psychology ◽  
Bayes Factor ◽  
Mixed Model ◽  
Factor Model ◽  
Source Code ◽  
Model Specification ◽  
Behavioral Sciences ◽  
Behavioral Experiments ◽  
Model Comparisons ◽  
Main Thesis

ANOVA---the workhorse of experimental psychology--seems well understood in that behavioral sciences have agreed-upon contrasts and reporting conventions. Yet, we argue this consensus hides considerable flaws in common ANOVA procedures, and these flaws become especially salient in the within-subject and mixed-model cases. The main thesis is that these flaws are in model specification. The specifications underlying common use are deficient from a substantive perspective, that is, they do not match reality in behavioral experiments. The problem, in particular, is that specifications rely on coincidental rather than robust statements about reality. We provide specifications that avoid making arguments based on coincidences, and note these Bayes factor model comparisons among these specifications are already convenient in the BayesFactor package. Finally, we argue that model specification necessarily and critically reflects substantive concerns, and, consequently, is ultimately the responsibility of substantive researchers. Source code for this project is at github/PerceptionAndCognitionLab/stat_aov2

scholarly journals Bayes Factor Model Comparisons Across Parameter Values for Mixed Models

2021 ◽  
Author(s):  
Maximilian Linde ◽  
Don van Ravenzwaaij
Keyword(s):  
Repeated Measures ◽  
Model Comparison ◽  
Bayes Factor ◽  
Factor Model ◽  
Simulated Data ◽  
Experimental Manipulation ◽  
Data Set ◽  
Model Comparisons ◽  
Multiple Data ◽  
Multiple Data Sets

AbstractNested data structures, in which conditions include multiple trials and are fully crossed with participants, are often analyzed using repeated-measures analysis of variance or mixed-effects models. Typically, researchers are interested in determining whether there is an effect of the experimental manipulation. These kinds of analyses have different appropriate specifications for the null and alternative models, and a discussion on which is to be preferred and when is sorely lacking. van Doorn et al. (2021) performed three types of Bayes factor model comparisons on a simulated data set in order to examine which model comparison is most suitable for quantifying evidence for or against the presence of an effect of the experimental manipulation. Here, we extend their results by simulating multiple data sets for various scenarios and by using different prior specifications. We demonstrate how three different Bayes factor model comparison types behave under changes in different parameters, and we make concrete recommendations on which model comparison is most appropriate for different scenarios.

Psychometrical Properties of a French Version of the General Self-Efficacy Short Scale (ASKU)

2020 ◽  
Vol 79 (1) ◽  
pp. 15-25
Author(s):  
Jean Philippe Décieux ◽  
Philipp Emanuel Sischka ◽  
Anette Schumacher ◽  
Helmut Willems
Keyword(s):  
Self Efficacy ◽  
Factor Model ◽  
German Version ◽  
French Version ◽  
Context Variable ◽  
Confirmatory Factor ◽  
French Speaking ◽  
German Speaking ◽  
Valid Instrument ◽  
General Self Efficacy

Abstract. General self-efficacy is a central personality trait often evaluated in surveys as context variable. It can be interpreted as a personal coping resource reflecting individual belief in one’s overall competence to perform across a variety of situations. The German-language Allgemeine-Selbstwirksamkeit-Kurzskala (ASKU) is a reliable and valid instrument to assess this disposition in the German-speaking countries based on a three-item equation. This study develops a French version of the ASKU and tests this French version for measurement invariance compared to the original ASKU. A reliable and valid French instrument would make it easy to collect data in the French-speaking countries and allow comparisons between the French and German results. Data were collected on a sample of 1,716 adolescents. Confirmatory factor analysis resulted in a good fit for a single-factor model of the data (in total, French, and German version). Additionally, construct validity was assessed by elucidating intercorrelations between the ASKU and different factors that should theoretically be related to ASKU. Furthermore, we confirmed configural and metric as well as scalar invariance between the different language versions, meaning that all forms of statistical comparison between the developed French version and the original German version are allowed.

Exploring the Multidimensional Facets of Authoritarianism: Authoritarian Aggression and Social Dominance Orientation

2008 ◽  
Vol 67 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Stefano Passini
Keyword(s):  
Social Dominance ◽  
Factor Model ◽  
Three Dimensional ◽  
Social Dominance Orientation ◽  
Model Fit ◽  
Regression Analyses ◽  
One Dimensional ◽  
Confirmatory Factor ◽  
The One ◽  
Better Than

The relation between authoritarianism and social dominance orientation was analyzed, with authoritarianism measured using a three-dimensional scale. The implicit multidimensional structure (authoritarian submission, conventionalism, authoritarian aggression) of Altemeyer’s (1981, 1988) conceptualization of authoritarianism is inconsistent with its one-dimensional methodological operationalization. The dimensionality of authoritarianism was investigated using confirmatory factor analysis in a sample of 713 university students. As hypothesized, the three-factor model fit the data significantly better than the one-factor model. Regression analyses revealed that only authoritarian aggression was related to social dominance orientation. That is, only intolerance of deviance was related to high social dominance, whereas submissiveness was not.

A Psychometric Study of the Quality Perception Questionnaire

2012 ◽  
Vol 71 (2) ◽  
pp. 101-106 ◽  
Author(s):  
Raffaele Cioffi† ◽  
Anna Coluccia ◽  
Fabio Ferretti ◽  
Francesca Lorini ◽  
Aristide Saggino ◽  
...  
Keyword(s):  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Fit Indices ◽  
Quality Perception ◽  
Italian Survey ◽  
Confirmatory Factor ◽  
Instrument Measuring ◽  
Hospital Structures

The present paper reexamines the psychometric properties of the Quality Perception Questionnaire (QPQ), an Italian survey instrument measuring patients’ perceptions of the quality of a recent hospital admission experience, in a sample of 4400 patients (Mage = 56.42 years; SD = 19.71 years, 48.8% females). The 14-item survey measures four factors: satisfaction with medical doctors, nursing staff, auxiliary staff, and hospital structures. First, we tested two models using a confirmatory factor analysis (structural equation modeling): a four orthogonal factor and a four oblique factor model. The SEM fit indices and the χ² difference suggested the acceptance of the second model. We then did a simulation using a bootstrap with 1000 replications. Results confirmed the four oblique factor solution. Third, we tested whether there were significant differences with respect to age or sex. The multivariate general linear model showed no significant differences in the factors with respect to sex or age.

Question Wording Effects in the Assessment of Global Self-Esteem

2000 ◽  
Vol 16 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Martin Dunbar ◽  
Graeme Ford ◽  
Kate Hunt ◽  
Geoff Der
Keyword(s):  
Reading Ability ◽  
Factor Model ◽  
Self Esteem ◽  
Reading Scores ◽  
Poor Reading ◽  
Method Effect ◽  
Two Samples ◽  
Positive Item ◽  
Method Effects ◽  
Best Fit

Summary: Marsh (1996) produced evidence that method effects associated with negatively worded items might be responsible for the results of earlier factor analytic studies that reported finding positive and negative self-esteem factors in the Rosenberg Global self-esteem scale ( Rosenberg, 1965 ). He analyzed data collected from children using a 7-item self-esteem measure. This report details attempts to replicate Marsh 's analysis in data collected from two samples of adults who completed the full 10-item Global Self-Esteem (GSE) scale. The results reported here are similar to those given by Marsh in so much as a correlated uniquenesses model produced a superior fit to the data than the simple one factor model (without correlated uniquenesses) or the often reported two factor (positive and negative self-esteem) model. However, whilst Marsh reported that the best fit was produced by allowing negative item uniquenesses to correlate with each other, the model that produced the best fit to these data was one that contained correlated positive item uniquenesses. Supporting his claim that differential responding to negative and positive self-esteem items reflects a method effect associated with reading ability, Marsh also showed that factors associated with negative and positive items were most distinct among children who had poor reading scores. We report a similar effect among a sample of older adults where the correlation between these factors was compared across two groups who were selected according to their scores on a test of verbal reasoning.

Social Desirability in Personality Inventories

2014 ◽  
Vol 35 (3) ◽  
pp. 144-157 ◽  
Author(s):  
Martin Bäckström ◽  
Fredrik Björklund
Keyword(s):  
Social Desirability ◽  
Big Five ◽  
Work Performance ◽  
Factor Model ◽  
Five Factor Model ◽  
Peer Ratings ◽  
Personality Inventories ◽  
Model Study ◽  
The Difference ◽  
New Variables

The difference between evaluatively loaded and evaluatively neutralized five-factor inventory items was used to create new variables, one for each factor in the five-factor model. Study 1 showed that these variables can be represented in terms of a general evaluative factor which is related to social desirability measures and indicated that the factor may equally well be represented as separate from the Big Five as superordinate to them. Study 2 revealed an evaluative factor in self-ratings and peer ratings of the Big Five, but the evaluative factor in self-reports did not correlate with such a factor in ratings by peers. In Study 3 the evaluative factor contributed above the Big Five in predicting work performance, indicating a substance component. The results are discussed in relation to measurement issues and self-serving biases.

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