Psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of Chilean university students
TL;DR: In this article, the authors evaluated the psychometric properties of the Multidimensional Students' Life Satisfaction Scale in a sample of university students from five state universities in Chile and found that the data fit better to the 30-items and five-factor structure than to the 40-item structure.
About: This article is published in Suma Psicológica.The article was published on 2017-07-01 and is currently open access. It has received 11 citations till now. The article focuses on the topics: Life satisfaction & Confirmatory factor analysis.
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01 Jan 2016
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14,604 citations
TL;DR: In this article, the authors evaluated the subjective well-being of 5189 school-going adolescents from 12 to 21 years old, using the Personal Wellbeing Index (PWI), performed by sex, place of residence, and by age groups.
12 citations
30 Dec 2020
TL;DR: In this article, the association between life satisfaction and subjective happiness while controlling for social desirability was investigated, with 279 participants from different universities of the Council of Rectors of Chile recruited through a non-pro-progressive study.
Abstract: The present study aimed at determining the association between life satisfaction and subjective happiness while controlling for social desirability, and to explore whether overall satisfaction with life can be predicted by satisfaction with life dimensions while controlling for social desirability. The study had a quantitative, non-experimental cross-sectional design, with 279 participants from different universities of the Council of Rectors of Chile recruited through a non-pro-
4 citations
Cites background from "Psychometric properties of the Mult..."
...Schnettler et al. (2017) reported adequate reliability indexes for Chilean university population (α = .88)....
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TL;DR: In this article, the authors evaluated the relationship between food satisfaction and family satisfaction and their relationships to university student life satisfaction, while also exploring the moderating role of the place of student residence, student self-health perception and the importance students assign to food in relation to well-being.
2 citations
TL;DR: In this paper, a set of rubrics were designed for formative purposes to help physical therapy students to acquire practical skills involved in neurological physical therapy (PT) and their application in the classroom, noting that students perceived them as valid, reliable, and highly useful for learning.
Abstract: One of the main challenges faced by physical therapy (PT) students is to learn the practical skills involved in neurological physical therapy (PT). To help them to acquire these skills, a set of rubrics were designed for formative purposes. This paper presents the process followed in the creation of these rubrics and their application in the classroom, noting that students perceived them as valid, reliable, and highly useful for learning. The perception of the validity and usefulness of the rubrics has different closely related dimensions, showing homogeneous values across the students´ sociodemographic and educational variables, with the exception of dedication to studying, which showed a significant relationship with schoolwork engagement and course satisfaction. The adequacy of the hypothesized structural model of the relationships among the variables was confirmed. Direct effects of the perception of the rubrics' validity and engagement on course satisfaction were found, as well as direct effects of the assessment of the usefulness of the rubrics on schoolwork engagement and indirect effects on course satisfaction through this latter variable. The results are discussed taking into account the conclusions of previous research and different instructional implications.
2 citations
References
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TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...
76,383 citations
"Psychometric properties of the Mult..." refers background or methods in this paper
...These indices are regarded as indicative of a good fit when GFI is greater than 0.90, AGFI greater than 0.80, CFI greater than 0.95, and RMSEA value is about 0.06 or lower (Hu & Bentler, 1999)....
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...Only the RMSEA value is close to the recommended value (Hu & Bentler, 1999)....
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...However, even though CFI, AGFI and CFI remain under the values recommended by Hu and Bentler (1999), it is noteworthy that the 2/df ratio indicates a good fit (Tabachnick & Fidell, 2001)....
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TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...
56,555 citations
"Psychometric properties of the Mult..." refers methods in this paper
...In the case of AVE values, the convergent validity of the construct was questionable....
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...When the AVE is less than 0.50, the variance due to measurement error is greater than the variance due to the construct....
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...AVE values were calculated for all five dimensions, but only the value for the subscale Friends was greater than 0.50 (Table 3)....
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...According to the results, the AVE of each pair of constructs was greater than its squared correlation, therefore discriminant validities were demonstrated in all the subscales....
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...In this study, discriminant validity was tested following Fornell and Larcker’s (1981), who compared the squared correlations between two constructs with their respective AVE. Discriminant validity is demonstrated if the AVE of both constructs is greater than its squared correlation....
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Book•
01 Jan 1983
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs
53,113 citations
Posted Content•
TL;DR: The Satisfaction With Life Scale is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness, but is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability.
Abstract: This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is suited for use with different age groups, and other potential uses of the scale are discussed.
21,449 citations
Additional excerpts
...It was developed by Diener et al. (1985)....
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TL;DR: The Satisfaction With Life Scale (SWLS) as mentioned in this paper is a scale to measure global life satisfaction, which does not tap related constructs such as positive affect or loneliness, and has favorable psychometric properties, including high internal consistency and high temporal reliability.
Abstract: This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is Suited for use with different age groups, and other potential uses of the scale are discussed.
20,751 citations