scholarly journals Adjusting for Measurement Noninvariance With Alignment Optimization in Growth Modeling

2021 ◽  
Author(s):  
Mark Lai
Keyword(s):  
Measurement Invariance ◽  
Growth Parameters ◽  
Growth Modeling ◽  
Growth Patterns ◽  
Longitudinal Measurement Invariance ◽  
Longitudinal Measurement ◽  
Partial Invariance ◽  
Simulation Results ◽  
Measurement Biases ◽  
Over Time

Longitudinal measurement invariance, the consistency of measurement in data collected over time, is a prerequisite for any meaningful inferences of growth patterns. When one or more items measuring the construct of interest shift its measurement properties over time, it leads to biased parameter estimates and inferences on the growth parameters. In this paper, we extended the recently-developed alignment optimization (AO) technique to adjust for measurement biases for growth models. The proposed AO method does not require identification of noninvariant items, and it can adjust for measurement biases even when all items are mild to moderately biased. We demonstrate how the proposed method can be implemented in the R statistical language using a textbook example, and conduct a Monte Carlo simulation study to compare its performance with the partial invariance modeling method. The simulation results show that alignment largely reduces biases in growth parameters and gives better control of Type I error rates, especially when the sample size is at least 1,000. It also outperforms the partial invariance method in conditions when all items are noninvariant. Based on the simulation results, we conclude that AO is a viable alternative to the partial invariance method in growth modeling when it is not clear whether longitudinal measurement invariance holds. Future research can further explore the potential of AO in other longitudinal models, such as alternative growth shapes and change score models.

scholarly journals Practical Significance of Longitudinal Measurement Invariance Violations in the Dutch–Flemish PROMIS Item Banks for Depression and Anxiety: An Illustration With Ordered-Categorical Data

Assessment ◽  
2019 ◽  
Vol 28 (1) ◽  
pp. 277-294
Author(s):  
Gerard Flens ◽  
Niels Smits ◽  
Caroline B. Terwee ◽  
Liv Pijck ◽  
Philip Spinhoven ◽  
...  
Keyword(s):  
Measurement Invariance ◽  
Practical Significance ◽  
Clinical Samples ◽  
Specific Response ◽  
Depression And Anxiety ◽  
Longitudinal Measurement Invariance ◽  
Longitudinal Measurement ◽  
Item Banks ◽  
The Impact ◽  
Over Time

We investigated longitudinal measurement invariance in the Dutch–Flemish PROMIS adult v1.0 item banks for Depression and Anxiety using two clinical samples with mood and anxiety disorders ( n = 640 and n = 528, respectively). Factor analysis was used to evaluate whether the item banks were sufficiently unidimensional at two test-occasions and whether the measured constructs remained the same over time. The results indicated that the item banks were sufficiently unidimensional, but the thresholds and residual variances of the constructs changed over time. However, using tentative rules of thumb, these invariance violations did not substantially affect the endorsement of a specific response category of a specific item at a specific test-occasion. Furthermore, the impact on the mean latent change scores of the item banks remained below the proposed cutoff value for substantial bias. These findings suggest that the invariance violations lacked practical significance for test-users, meaning that the item banks provide sufficiently invariant latent factor scores for use in clinical practice.

scholarly journals Measuring depression over time . . . Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression.

2016 ◽  
Vol 28 (11) ◽  
pp. 1354-1367 ◽  
Author(s):  
Eiko I. Fried ◽  
Claudia D. van Borkulo ◽  
Sacha Epskamp ◽  
Robert A. Schoevers ◽  
Francis Tuerlinckx ◽  
...  
Keyword(s):  
Measurement Invariance ◽  
Rating Scales ◽  
Longitudinal Measurement Invariance ◽  
Longitudinal Measurement ◽  
Over Time

scholarly journals 0551 Longitudinal Measurement Invariance of the Insomnia Severity Index in Veterans with Sleep Apnea

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A211-A211
Author(s):  
W Wohlgemuth ◽  
A Fins ◽  
J Tutek ◽  
A Gonzalez ◽  
A Martinez-Garcia ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Measurement Invariance ◽  
Factor Model ◽  
Severity Index ◽  
Equation Modeling ◽  
Longitudinal Measurement Invariance ◽  
Insomnia Severity Index ◽  
Longitudinal Measurement ◽  
Insomnia Severity ◽  
Over Time

Abstract Introduction The Insomnia Severity Index is a commonly used instrument to assess the presence of insomnia symptoms as well as an outcome measure following an intervention. Longitudinal measurement invariance is a necessary property of an assessment instrument when it is repeated over time. The validity of conclusions regarding change in the construct ‘insomnia severity’ depend on scale equivalence at each measurement timepoint. Assessment of measurement invariance of the ISI in sleep apnea patients has never been performed. Methods Veterans with sleep apnea (n=654; AHI=36±28; 93% male; age=52±12; BMI=33±6) completed the ISI on the night of their overnight PSG and again when they picked up their PAP device. Invariance was determined by imposing a series of more restrictive equivalence constraints on a 2-factor model of the ISI. The series of constraints tested for configural, weak, strong and strict invariance. Invariance testing was modeled with exploratory structural equation modeling in Mplus (v. 7.0). Results The 2-factor model that emerged from the analysis showed items relating to nighttime symptoms loading on factor 1 and daytime symptoms loading on factor 2. The sleep ‘satisfaction’ item, however, had weak but similar loadings on both factors. The increasingly restrictive constraints imposed on the model revealed no decrement in model fit (RMSEA=.039 to.043; CFI=.987 to .980; TLI=.981-.977; SRMR=.027-.041). Conclusion The ISI met strict criteria for longitudinal measurement invariance demonstrating that it is a valid instrument to be used in repeated measures study designs of insomnia in sleep apnea patients. Change over time on the ISI is not due to the changing measurement characteristics of the ISI but to true changes in the ‘insomnia severity’ construct. Support None

Longitudinal Measurement Invariance of the PHQ-9 and GAD-7

Assessment ◽  
2021 ◽  
pp. 107319112110358
Author(s):  
Clarissa W. Ong ◽  
Benjamin G. Pierce ◽  
Keith P. Klein ◽  
Chloe C. Hudson ◽  
Courtney Beard ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Measurement Invariance ◽  
Generalized Anxiety Disorder ◽  
Generalized Anxiety ◽  
Health Questionnaire ◽  
Longitudinal Measurement Invariance ◽  
Partial Hospital ◽  
Longitudinal Measurement ◽  
Patient Health ◽  
Over Time

Intraindividual change over time is commonly used to estimate treatment effectiveness. However, patients may not respond similarly to a scale after treatment, rendering pre–post change an unreliable metric. The current objective was to investigate longitudinal measurement invariance of the Patient Health Questionnaire–9 and Generalized Anxiety Disorder Scale–7 among 4,323 patients completing a partial hospital program. We used confirmatory factor analysis to determine (1) factor structure at pretreatment and posttreatment and (2) longitudinal invariance, accounting for dependent observations, using both classical and approximate measurement invariance approaches. Results indicated a two-factor solution for both scales. Longitudinal invariance was not established for either scale, thus, using raw score differences from the Patient Health Questionnaire–9 and Generalized Anxiety Disorder Scale–7 for measuring symptom change over time may be problematic. The most longitudinally consistent items captured somatic as opposed to affective/cognitive symptoms. We discuss the potential use of these measures for diagnostic screening and between-group comparisons and suggest alternative ways to monitor client progress over time. Limitations included a majority White sample and uniqueness of a partial hospital setting.

Assessing Family Outcomes Over Time: Longitudinal Measurement Invariance of the Family Outcomes Survey–Revised

2021 ◽  
pp. 027112142199083
Author(s):  
Nicolette Waschl ◽  
Kenneth K. Poon ◽  
Mo Chen ◽  
Huichao Xie
Keyword(s):  
Measurement Invariance ◽  
Developmental Delays ◽  
Change Scores ◽  
Family Outcomes ◽  
Early Intervention Services ◽  
Longitudinal Measurement Invariance ◽  
Longitudinal Measurement ◽  
The Family ◽  
Family Outcome ◽  
Over Time

The Family Outcomes Survey–Revised (FOS-R) measures family outcomes of services for young children with disabilities or developmental delays, and can be used to investigate change in outcome achievement over time. To confirm the validity of FOS-R change scores, it must be established that the FOS-R measures the same construct over time; if so, score changes can be attributed to family outcome achievement. However, if not, interpretation of change scores may be misleading. Caregivers ( N = 349) of Singaporean children with developmental delays receiving early intervention services completed the FOS-R Part A twice, approximately 1 year apart. Factor analysis was used to confirm the structure of the FOS-R Part A and to assess whether the scale measures the same thing across time (i.e., longitudinal measurement invariance). Results provided support for partial longitudinal measurement invariance, indicating that change scores on this scale can be validly interpreted with certain caveats.

Longitudinal and Gender Measurement Invariance of the Gratitude Questionnaire in Chinese Adolescents

2021 ◽  
pp. 003329412110360
Author(s):  
Qingsong Tan ◽  
Jilin Zou ◽  
Feng Kong
Keyword(s):  
Measurement Invariance ◽  
Time Interval ◽  
Longitudinal Measurement Invariance ◽  
Multiple Group ◽  
Longitudinal Measurement ◽  
Confirmatory Factor ◽  
Adolescent Sample ◽  
Good Internal Consistency ◽  
And Gender ◽  
Mean Differences

The 5-item Gratitude Questionnaire (GQ-5) is one of the most commonly used instruments to measure dispositional gratitude in adolescents. The purpose of this study was to verify the longitudinal measurement invariance (LMI) and gender measurement invariance (GMI) of the GQ-5 that was administered to an adolescent sample twice over the course of 18 months ( N = 669). Single-group confirmatory factor analysis (CFA) was adopted to examine the LMI and multiple-group CFA was conducted to assess the GMI. The results showed that the GQ-5 had strong invariance (i.e., equality of factor patterns, loadings, and intercepts) across time and gender. Validation of latent factor mean differences showed that females had higher gratitude scores than males. In addition, the GQ-5 exhibited good internal consistency indices across time and a moderate stability coefficient was also found across an 18-month time interval in adolescents. In summary, our study showed that LMI and GMI of the GQ-5 are satisfactory and the GQ-5 is a reliable instrument for measuring gratitude in adolescents.

Longitudinal Measurement Invariance of Beck Depression Inventory–II in Early Adolescents

Assessment ◽  
2016 ◽  
Vol 24 (3) ◽  
pp. 337-345 ◽  
Author(s):  
Pei-Chen Wu
Keyword(s):  
High School Students ◽  
Measurement Invariance ◽  
Beck Depression Inventory ◽  
Factor Model ◽  
Early Adolescents ◽  
Series Data ◽  
Data Sets ◽  
Longitudinal Measurement Invariance ◽  
Longitudinal Measurement ◽  
Three Factor

This study explored the longitudinal measurement invariance in the Beck Depression Inventory–II (BDI-II) in early adolescents (junior high school students). The participants were 730 early adolescents (330 boys and 400 girls), who were followed up over 3 years (in six waves). To reduce the size of longitudinal model and verify the stability of the findings, the Fall and Spring series data sets were analyzed separately. Each series includes three waves of data with about 1-year apart. It was found that the three-factor model (Negative Attitude, Performance Difficulty, and Somatic Elements) best fitted the data. Results of both data sets provided support for the longitudinal measurement invariance (threshold invariance) of the three-factor model, suggesting that the BDI-II measured the same construct over 3 years. The study also examined the category function of the BDI-II on the basis of the pattern of threshold estimates. Finally, the implications of the findings on the continuing use of the BDI-II are discussed.

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