scholarly journals Estimating the stability of the number of factors via Bootstrap Exploratory Graph Analysis: A tutorial

2019 ◽  
Author(s):  
Alexander P. Christensen ◽  
Hudson Golino
Keyword(s):  
Factor Analysis ◽  
Graph Analysis ◽  
Real World Data ◽  
Popular Approach ◽  
Robust Approach ◽  
Number Of Factors ◽  
Bootstrap Approach ◽  
Recent Addition ◽  
The Stability ◽  
Stability Statistics

Exploratory graph analysis (EGA) is a recent addition to the growing field of network psychometrics. EGA has emerged as a popular approach for estimating the dimensonality of data in networks. The appeal of EGA is the visualization of the relations between variables and the deterministic allocation of variables into dimensions. Notably, networks tend to be sample-specific, making reproducibility and generalizability a key issue in network psychometrics. To resolve this issue, we’ve developed a novel bootstrap approach called, Bootstrap Exploratory Graph Analysis (bootEGA). bootEGA provides researchers with dimension and item stability statistics as well as item analyses that are akin to exploratory factor analysis loadings. We provide descriptions of bootEGA’s functions accompanied by a step-by-step R tutorial for how to apply and interpret bootEGA’s results. This tutorial is applied to real-world data to demonstrate its effectiveness at identifying problematic dimensions and items. In short, our results show that bootEGA is a robust approach for identifying the stability and robustness of dimensionality in data.

scholarly journals Estimating the Stability of Psychological Dimensions via Bootstrap Exploratory Graph Analysis: A Monte Carlo Simulation and Tutorial

Psych ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 479-500
Author(s):  
Alexander P. Christensen ◽  
Hudson Golino
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Multivariate Data ◽  
Semantic Content ◽  
Graph Analysis ◽  
Bootstrap Approach ◽  
Structural Consistency ◽  
The Stability ◽  
Stability Statistics ◽  
Psychological Dimensions

Exploratory Graph Analysis (EGA) has emerged as a popular approach for estimating the dimensionality of multivariate data using psychometric networks. Sampling variability, however, has made reproducibility and generalizability a key issue in network psychometrics. To address this issue, we have developed a novel bootstrap approach called Bootstrap Exploratory Graph Analysis (bootEGA). bootEGA generates a sampling distribution of EGA results where several statistics can be computed. Descriptive statistics (median, standard error, and dimension frequency) provide researchers with a general sense of the stability of their empirical EGA dimensions. Structural consistency estimates how often dimensions are replicated exactly across the bootstrap replicates. Item stability statistics provide information about whether dimensions are unstable due to misallocation (e.g., item placed in the wrong dimension), multidimensionality (e.g., item belonging to more than one dimension), and item redundancy (e.g., similar semantic content). Using a Monte Carlo simulation, we determine guidelines for acceptable item stability. After, we provide an empirical example that demonstrates how bootEGA can be used to identify structural consistency issues (including a fully reproducible R tutorial). In sum, we demonstrate that bootEGA is a robust approach for identifying the stability and robustness of dimensionality in multivariate data.

Factor Analysis of the Stability of Self Scale

1980 ◽  
Vol 47 (3_suppl) ◽  
pp. 1160-1162 ◽  
Author(s):  
Stephen L. Franzoi ◽  
Benjamin J. Reddish
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Principal Components ◽  
Analysis Data ◽  
Factor Solution ◽  
The Stability

The factor structure of Rosenberg's Stability of Self Scale (1965) was investigated via principal components factor analysis. Data from 92 male and 171 female undergraduates yielded a one-factor solution, supporting Rosenberg's contention that the scale is unidimensional.

Validation of the Beliefs of Physical Activity among Clergy (B-PAC) Instrument

2017 ◽  
Vol 32 (2) ◽  
Author(s):  
Shannon Gwin ◽  
Paul Branscum ◽  
E. Laurette Taylor
Keyword(s):  
Physical Activity ◽  
Factor Analysis ◽  
Construct Validity ◽  
Psychometric Properties ◽  
Internal Consistency ◽  
Internal Consistency Reliability ◽  
Retest Reliability ◽  
Reliable Instrument ◽  
The Stability ◽  
Test Retest Reliability

The purpose of this study was to create a valid and reliable instrument to evaluate theory-basedbeliefs towards physical activity among clergy members. Data were collected from 174 clergy that par-ticipated in a 15-item online and paper-based survey. Psychometric properties of the instrument includedconfirmatory factor analysis (construct validity), and cronbach’s alpha (internal consistency reliability).In addition, the stability (test-retest reliability) of each subscale was evaluated with a sub-sample of 30participants. Results show the instrument was both valid and reliable, and will be useful in future studiestargeting this population. Future implications are discussed.

scholarly journals PATACSDB - The database of polyA translational attenuators in coding sequences

2015 ◽  
Author(s):  
Malgorzata Habich ◽  
Sergej Djuranovic ◽  
Pawel Szczesny
Keyword(s):  
Gene Dosage ◽  
Interesting Case ◽  
Minimal Length ◽  
Regulatory Mechanisms ◽  
Coding Sequences ◽  
Translation Apparatus ◽  
Recent Addition ◽  
Dosage Balance ◽  
The Stability ◽  
Eukaryotic Genomes

Recent addition to the repertoire of gene expression regulatory mechanisms are polyadenylate (polyA) tracks encoding for poly-lysine runs in protein sequences. Such tracks stall translation apparatus and induce frameshifting independently of the effects of charged nascent poly-lysine sequence on the ribosome exit channel. As such they substantially influence the stability of mRNA and amount of protein produced from a given transcript. Single base changes in these regions are enough to exert a measurable response on both protein and mRNA abundance, and makes each of these sequences potentially interesting case studies for effects of synonymous mutation, gene dosage balance and natural frameshifting. Here we present the PATACSDB, a resource that contain comprehensive list of polyA tracks from over 250 eukaryotic genomes. Our data is based on Ensembl genomic database of coding sequences and filtered with algorithm of 12A-1 which selects sequences of polyA tracks with a minimal length of 12 A's allowing for one mismatched base. The PATACSDB database is accesible at: http://sysbio.ibb.waw.pl/patacsdb. Source code is available for download from GitHub repository at http://github.com/habich/PATACSDB, including the scripts to recreate the database from the scratch on user's own computer.

scholarly journals Entropy Fit Indices: New Fit Measures for Assessing the Structure and Dimensionality of Multiple Latent Variables.

2019 ◽  
Author(s):  
Hudson Golino ◽  
Robert Glenn Moulder ◽  
Dingjing Shi ◽  
Alexander P. Christensen ◽  
Luis E. Garrido ◽  
...  
Keyword(s):  
Information Theory ◽  
Quantum Information ◽  
Latent Variables ◽  
Categorical Variables ◽  
Graph Analysis ◽  
Fit Indices ◽  
Latent Factors ◽  
Accurate Identification ◽  
Number Of Factors ◽  
Fit Index

The accurate identification of the content and number of latent factors underlying multivariate data is an important endeavor in many areas of Psychology and related fields. Recently, a new dimensionality assessment technique based on network psychometrics was proposed (Exploratory Graph Analysis, EGA), but a measure to check the fit of the dimensionality structure to the data estimated via EGA is still lacking. Although traditional factor-analytic fit measures are widespread, recent research has identified limitations for their effectiveness in categorical variables. Here, we propose three new fit measures (termed entropy fit indices) that combines information theory, quantum information theory and structural analysis: Entropy Fit Index (EFI), EFI with Von Neumman Entropy (EFI.vn) and Total EFI.vn (TEFI.vn). The first can be estimated in complete datasets using Shannon entropy, while EFI.vn and TEFI.vn can be estimated in correlation matrices using quantum information metrics. We show, through several simulations, that TEFI.vn, EFI.vn and EFI are as accurate or more accurate than traditional fit measures when identifying the number of simulated latent factors. However, in conditions where more factors are extracted than the number of factors simulated, only TEFI.vn presents a very high accuracy. In addition, we provide an applied example that demonstrates how the new fit measures can be used with a real-world dataset, using exploratory graph analysis.

scholarly journals Adaptasi Sanctification of Marriage Questionnaire: Versi Indonesia untuk Masyarakat Muslim

2021 ◽  
Vol 26 (1) ◽  
pp. 217-232
Author(s):  
Hepi Wahyuningsih ◽  
Dyna Rahayu Suci Pertiwi
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Structure Stability ◽  
Validity And Reliability ◽  
Confirmatory Factor ◽  
The Stability ◽  
Composite Reliability

This study aims to adapt the Sanctification of Marriage Questionnaire for Muslims inIndonesia. Adaptation of the Sanctification of Marriage Questionnaire is carried out throughthe stages: translation, providing evidence of construct validity and reliability. Evidence of construct validity was carried out by exploratory factor analysis followed by MGCFA (Multi-Group Confirmatory factor Analysis). In this study, we used a composite reliability. Subjects to reveal the factor structure of sanctification of marriage were 160 married individuals, while the subjects to test the stability of factor structure consisted of 102 husbands and 111 wives. The result of exploratory factor analysis shows that the construct of sanctification of marriage has three factors / dimensions, namely: belief, perceived sacred qualities and manifestation of God. The structure stability of sanctification of marriage was then empirically tested by MGCFA. The results of MGCFA showed that the three factors / dimensions of sanctification of marriage proved stable. The composite reliability coefficient of the Sanctification of Marriage Questionnaire was in a good category. Further research can be carried out to provide evidence of construct validity with predictive validity and concurrent validity of the Sanctification of Marriage Questionnaire. Limitations in this study are discussed further.Keywords: exploratory factor analysis, multi-group confirmatory factor analysis, muslim,sanctification of marriage, scale adaptation

scholarly journals Validity and Reliability Study of the Scale for Determining the Civic-mindedness Levels of Teaching Staff

2017 ◽  
Vol 5 (4) ◽  
pp. 44
Author(s):  
Rüştü Yeşil
Keyword(s):  
Factor Analysis ◽  
Correlation Coefficients ◽  
Teaching Staff ◽  
Validity And Reliability ◽  
Cronbach’S Alpha ◽  
Cronbach's Alpha ◽  
Bartlett Test ◽  
Development Participation ◽  
The Stability ◽  
Civic Mindedness

use after also being checked by linguists. The validity analysis of the scale for the data collected was performed with exploratory factor analysis and item-total correlation tests, while the property of reliability was determined using the Cronbach’s alpha internal consistency coefficient and the stability test was carried out by determining the relationship between two applications conducted at an interval of the five weeks. The scale, which is called the “Scale for Determining the Civic-Mindedness Levels of Individuals” is a five-step Likert-type scale and consists of 27 items that can be collected under three factors. The factor names are “Openness to Criticism/Development”, “Participation/Activeness” and “Lack of Prejudice/Flexibility”. The KMO value of the scale was 0.956; and the Bartlett Test values were x2=11001.719; sd=351; p<0.000. Items in the scale accounted for 56.619% of the total variance. As a result of the confirmatory factor analysis, the χ2 value was 808.07 and the degree of freedom was 321. Χ2/df is 2.51. The fit indices of the scale were determined as RMSEA=0.067; S-RMR=0.049; NFI=0.97. The item-total corrected correlation coefficients of the items in the scale varied between 0.40 and 0.703 (p<.01). The reliability coefficient of the scale was Cronbach’s alpha at 0.954 and the stability coefficients of the items were between 0.496 and 0.674 (p<,01).

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