Latent variable path analysis in clinical research: A beginner's tour guide

1991 ◽  
Vol 47 (4) ◽  
pp. 471-484 ◽  
Author(s):  
Rex B. Kline
Keyword(s):  
Clinical Research ◽  
Path Analysis ◽  
Latent Variable ◽  
Tour Guide ◽  
Latent Variable Path Analysis ◽  
Latent Variable Path

scholarly journals Impact of the stringency of lockdown measures on covid-19: A theoretical model of a pandemic

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258205
Author(s):  
Claudio Violato ◽  
Emilio Mauro Violato ◽  
Efrem Mauro Violato
Keyword(s):  
Theoretical Model ◽  
Path Analysis ◽  
Multiple Regression ◽  
Latent Variable ◽  
Mortality Rates ◽  
Infection Rates ◽  
Public Data ◽  
Latent Variable Path Analysis ◽  
Latent Variable Path ◽  
Infection Spread

Background How effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling. Methods Lockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis. Results Multiple regression indicated that the time from lockdown had a small but significant effect (β = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (β = 0.588,β = 0.702, β = 0.518, β = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08). Discussion The stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.

School belonging in adolescents: Psychometric properties of the School Belongingness Scale in Iranian students

2020 ◽  
pp. 1-10 ◽  
Author(s):  
Gökmen Arslan ◽  
Faramarz Asanjarani ◽  
Saeede Bakhtiari ◽  
Fatemeh Hajkhodadadi
Keyword(s):  
Psychometric Properties ◽  
Latent Variable ◽  
Measurement Model ◽  
Social Emotional ◽  
School Belongingness ◽  
Confirmatory Factor ◽  
Factor Measurement ◽  
Latent Variable Path Analysis ◽  
Iranian Students ◽  
Latent Variable Path

Abstract The purpose of the present study is to investigate the initial psychometric properties and cultural adaptation of the School Belongingness Scale (SBS) in a sample of Iranian adolescents. Participants included 324 students, ranging in age between 12 and 18 years (M = 14.68, SD = 1.39). Confirmatory factor analysis indicated that responses to the Farsi version of the SBS were characterised by a two-factor measurement model, and latent variable path analysis results revealed this measurement model was predictive of adolescents’ responses to measures of social, emotional, and behavioural problems (e.g., emotional problems, conduct problems), academic achievement, and prosocial behaviour. These results provide initial evidence suggesting that the scale is psychometrically adequate to measure Iranian students’ sense of belonging at school.

Latent Variable Path Modeling with Partial Least Squares

Technometrics ◽  
1992 ◽  
Vol 34 (1) ◽  
pp. 110 ◽  
Author(s):  
Charles K. Bayne ◽  
Jan-Bernd Lohmöller ◽  
Jan-Bernd Lohmoller
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variable ◽  
Path Modeling ◽  
Latent Variable Path

scholarly journals Student Ratings of Teaching Effectiveness: Student Engagement and Course Characteristics

2010 ◽  
Vol 39 (1) ◽  
Author(s):  
Tanya Beran ◽  
Claudio Violato
Keyword(s):  
Student Engagement ◽  
Latent Variable ◽  
Teaching Effectiveness ◽  
Student Ratings ◽  
Path Model ◽  
Course Characteristics ◽  
Student Ratings Of Instruction ◽  
Fit Index ◽  
Student Ratings Of Teaching ◽  
Latent Variable Path

Characteristics of university courses and student engagement were examined in relation to student ratings of instruction. The Universal Student Ratings of Instruction instrument was administered to students at the end of every course at a major Canadian university over a three-year period. Using a two-step analytic procedure, a latent variable path model was created. The model showed a moderate fit to the data (Comparative Fit Index = .88), converged in _0 iterations, with a standardized residual mean error of .03, χ2 (_49) = _988.59, p < .05. The model indicated that course characteristics such as status and description are not directly related to student ratings. Rather, they are mediated by student engagement, which is measured by student attendance and expected grade. It was concluded that, although the model is statistically adequate, many other factors determine how students rate their instructors.  

scholarly journals A Method for Examining the Equating of Psychometric Scales and Tests: An Application Using Dementia Screening Test Batteries

2018 ◽  
Vol 80 (1) ◽  
pp. 199-209
Author(s):  
N. Maritza Dowling ◽  
Tenko Raykov ◽  
George A. Marcoulides
Keyword(s):  
Clinical Research ◽  
Empirical Research ◽  
Screening Test ◽  
Latent Variable ◽  
Necessary Condition ◽  
Measuring Instruments ◽  
Psychometric Scales ◽  
Latent Constructs ◽  
Dementia Screening ◽  
Wide Range

Equating of psychometric scales and tests is frequently required and conducted in educational, behavioral, and clinical research. Construct comparability or equivalence between measuring instruments is a necessary condition for making decisions about linking and equating resulting scores. This article is concerned with a widely applicable method for examining if two scales or tests cannot be equated. A latent variable modeling method is discussed that can be used to evaluate whether the tests or parts thereof measure latent constructs that are distinct from each other. The approach can be routinely used before an equating procedure is undertaken, in order to assess whether equating could be meaningfully carried out to begin with. The procedure is readily applicable in empirical research using popular software. The method is illustrated with data from dementia screening test batteries administered as part of two studies designed to evaluate a wide range of biomarkers throughout the process of normal aging to dementia or Alzheimer’s disease.

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