Evaluate Model Fit Research Articles

Documenting and modeling the acoustic variability of intervocalic alveolar taps in conversational Peninsular Spanish.

This study constitutes an investigation into the acoustic variability of intervocalic alveolar taps in a corpus of spontaneous speech from Madrid, Spain. Substantial variability was documented in this segment, with highly reduced variants constituting roughly half of all tokens during spectrographic inspection. In addition to qualitative documentation, the intensity difference between the tap and surrounding vowels was measured. Changes in this intensity difference were statistically modeled using Bayesian finite mixture models containing lexical and phonetic predictors. Model comparisons indicate predictive performance is improved when we assume two latent categories, interpreted as two pronunciation variants for the Spanish tap. In interpreting the model, predictors were more often related to categorical changes in which pronunciation variant was produced than to gradient intensity changes within each tap type. Variability in tap production was found according to lexical frequency, speech rate, and phonetic environment. These results underscore the importance of evaluating model fit to the data as well as what researchers modeling phonetic variability can gain in moving past linear models when they do not adequately fit the observed data.

A Unified Dynamic Model for the Decomposition of Skin Conductance and the Inference of Sudomotor Nerve Activities.

Electrodermal activity (EDA), commonly measured as skin conductance (SC), is a widely used physiological signal in psychological research and behavioral health applications. EDA is considered an indicator of arousal, a key aspect of emotion and stress. This work proposes a data-driven dynamic system model that characterizes the temporal dynamics of skin conductance and infers the latent arousal signal, utilizing techniques from system identification and sparse optimization. It introduces a fourth-order, linear time-invariant model for the overall skin conductance signal, including both the tonic and phasic components. The model was applied to a large dataset of over 200 participants to evaluate model fit. Furthermore, a three-component decomposition of skin conductance is introduced, based on mathematical definitions derived from the model, which provides key insights into the temporal dynamics of skin conductance. Comparative evaluation shows that the estimated latent neural signal effectively differentiates between high and low arousal states, while maintaining expected physiological properties. This work lays the foundation for numerous behavioral health applications and paves the road for designing physiology-based interventions aimed at regulating arousal.

NORMATIVE VALUES FOR STRENGTH AND FUNCTION DERIVED FROM THE CANADIAN LONGITUDINAL STUDY ON AGING

Abstract Decreased muscle strength and physical function often precede disability, nursing home admission, home care use, and mortality in older adults. Normative values for commonly used physical performance-based tests are not widely available for older adults but are required for clinicians and researchers to easily identify individuals with low performance. Our objective was to develop normative values for grip strength, gait speed, Timed Up and Go, single leg balance, and five-repetition chair rise tests in a large population-based sample of Canadians aged 45 to 85 years. Baseline data (2011-2015) from the Canadian Longitudinal Study on Aging was used to estimate age- and sex-specific normative values for each of the physical tests. Participants were without disability or mobility limitation (no assistance with activities of daily living or use of mobility devices). Of the 25,470 participants eligible for the analyses 48.6% (n=12,369) were female with a mean age of 58.6 ±9.5 years. Sex-specific 5th, 10th, 20th, 50th, 80th, 90th, and 95th percentile values for each physical performance-based test were estimated. Cross-validation (n=100 repetitions) with a 30% holdout sample was used to evaluate model fit. The normative values developed in this paper can be used in clinical and research settings to identify individuals with low performance relative to their peers of the same age and sex. Interventions targeting these at-risk individuals including physical activity can prevent or delay mobility disability and the resulting cascade of increasing care requirements, health care costs, and mortality.

Seeing the impossible: Visualizing latent variable models with flexplavaan.

Latent variable models (LVMs) are incredibly flexible tools that allow users to address research questions they might otherwise never be able to answer (McDonald, 2013). However, one major limitation of LVMs is evaluating model fit. There is no universal consensus about how to evaluate model fit, either globally or locally. Part of the reason evaluating these models is difficult is because fit is typically reduced to a handful of statistics that may or may not reflect the model's adequacy and/or assumptions. In this article we argue that proper evaluation of model fit must include visualizing both the raw data and the model-implied fit. Visuals reveal, at a glance, the fit of the model and whether the model's assumptions have been met. Unfortunately, tools for visualizing LVMs have historically been limited. In this article, we introduce new plots and reframe existing plots that provide necessary resources for evaluating LVMs. These plots are available in a new open-source R package called flexplavaan, which combines the model plotting capabilities of flexplot with the latent variable modeling capabilities of lavaan. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The relationship between depression and sexual satisfaction: An equation model analysis

BACKGROUND: The relationship between depression and sexual satisfaction in middle-aged women has been reported previously. However, there is insufficient evidence that depression is related to sexual satisfaction or that sexual satisfaction is related to depression. This study evaluated the relationship between depression and sexual satisfaction in middle-aged women by evaluating the equation model analysis of the two models. MATERIALS AND METHODS: This cross-sectional study was conducted on 190 middle-aged women in Isfahan, Iran, in 2021. Sexual satisfaction dimensions were evaluated using self-report women's sexual satisfaction questionnaire. Also, the depression scale of the general health questionnaire was used to measure of the depression level. Research data were analyzed using a multivariate linear regression test. Also, the fit of the model was evaluated using Amos software. RESULTS: The results showed that depression score had an inverse relationship with sexual satisfaction in the relational concern dimension (Beta = −0.27, P = 0.006, CI: −0.11 to − 0.86). Model fit evaluation showed that the sexual satisfaction-depression model had a better fit than the depression-sexual satisfaction model (CMIN/DF = 1.123, P = 0.64). CONCLUSION: The results showed that depression in middle-aged women is related to the relational concern. It is necessary to consider counseling programs to solve sexual relationship concerns in middle-aged women's mental health promotion programs.

Development and validation of the COVID-19 Impact Scale in Australia

Objective The COVID-19 pandemic significantly impacted and continues to impact the health and well-being of Australian adults. However, there has been no instrument validated to comprehensively measure how the COVID-19 pandemic impacted adults in Australia across several domains (e.g. fear of COVID-19, attitudes towards vaccination, psychosocial impact of lockdowns). The current study conducted a rigorous psychometric process to develop and validate an instrument to measure the impact of the COVID-19 pandemic in Australia, the COVID-19 Impact Scale (CIS). Method Data was obtained from the Australian population. Participants (N = 563) aged between 19 and 91 years (M = 54.50, SD = 16.16) provided online responses between June, 2021 and May, 2022. The majority of participants were female (60.9%), employed either full-time (37.7%) or part-time (22.0%), and had completed an undergraduate degree or higher (70.1%). An initial pool of 30 items was developed based on a review of the literature and input from a panel of experts including psychologists, epidemiologists, and public health experts, among others. The study used network psychometrics to examine the psychometric properties of: (1) item score distributions; (2) item redundancy; (3) dimensionality; (4) model fit; (5) measurement invariance; (6) reliability; and (7) criterion validity. Results Following an evaluation of items for ceiling/floor effects and redundancy, the final CIS network model included eighteen nodes and displayed a three-dimensional structure. The three communities of “Fear” (consisting of three nodes; ω = 0.82), “Attitudes” (consisting of ten nodes; ω = 0.89), and “Ill-being” (consisting of five nodes; ω = 0.79) displayed adequate reliability. The evaluation of model fit indicated a good fit of the network model (RMSEA = 0.047; CFI =0.98). Conclusion The instrument is available to be used by Australian researchers and implemented to evaluate public policies, adapted for future pandemics, or used internationally.

Validation of the Guess-18 for Video Game Players with Disabilities

The purpose of this study is to determine if the game satisfaction scale, the GUESS-18, factors are valid for video gamers with disabilities. Participants were asked to evaluate a video game of their choice using the GUESS-18 and answer qualitative questions about the clarity of the items, requirements needed in order to play a video game, and aspects of video games they liked and disliked. A confirmatory factor analysis (CFA, N = 414) was used to evaluate model fit, and an analysis of the qualitative data was conducted. The CFA determined that the GUESS-18 is appropriate for use with this population, and analysis of the qualitative data determined that participants reported GUESS-18 statement items to be easy to understand. 82.29% of participant comments were mapped to GUESS-18 items, while the remaining statements were mapped to the original GUESS, GUESS factors, or were deemed Not Applicable or Not Enough Information.

Why we need to abandon fixed cutoffs for goodness-of-fit indices: An extensive simulation and possible solutions

To evaluate model fit in confirmatory factor analysis, researchers compare goodness-of-fit indices (GOFs) against fixed cutoff values (e.g., CFI > .950) derived from simulation studies. Methodologists have cautioned that cutoffs for GOFs are only valid for settings similar to the simulation scenarios from which cutoffs originated. Despite these warnings, fixed cutoffs for popular GOFs (i.e., χ2, χ2/df, CFI, RMSEA, SRMR) continue to be widely used in applied research. We (1) argue that the practice of using fixed cutoffs needs to be abandoned and (2) review time-honored and emerging alternatives to fixed cutoffs. We first present the most in-depth simulation study to date on the sensitivity of GOFs to model misspecification (i.e., misspecified factor dimensionality and unmodeled cross-loadings) and their susceptibility to further data and analysis characteristics (i.e., estimator, number of indicators, number and distribution of response options, loading magnitude, sample size, and factor correlation). We included all characteristics identified as influential in previous studies. Our simulation enabled us to replicate well-known influences on GOFs and establish hitherto unknown or underappreciated ones. In particular, the magnitude of the factor correlation turned out to moderate the effects of several characteristics on GOFs. Second, to address these problems, we discuss several strategies for assessing model fit that take the dependency of GOFs on the modeling context into account. We highlight tailored (or “dynamic”) cutoffs as a way forward. We provide convenient tables with scenario-specific cutoffs as well as regression formulae to predict cutoffs tailored to the empirical setting of interest.

Predicting hospital readmission in Medicaid patients with diabetes using administrative and claims data.

Readmission is common and costly for hospitalized Medicaid patients with diabetes. We aimed to develop a model predicting risk of 30-day readmission in Medicaid patients with diabetes hospitalized for any cause. Using 2016-2019 Medicaid claims from 7 US states, we identified patients who (1) had a diagnosis of diabetes or were prescribed any diabetes drug, (2) were hospitalized for any cause, and (3) were discharged to home or to a nonhospice facility. For each encounter, we assessed whether the patient was readmitted within 30 days of discharge. Applying least absolute shrinkage and selection operator variable selection, we included demographic data and claims history in a logistic regression model to predict 30-day readmission. We evaluated model fit graphically and measured predictive accuracy by the area under the receiver operating characteristic curve (AUROC). Among 69,640 eligible patients, there were 129,170 hospitalizations, of which 29,410 (22.8%) were 30-day readmissions. The final model included age, sex, age-sex interaction, past diagnoses, US state of admission, number of admissions in the preceding year, index admission type, index admission diagnosis, discharge status, length of stay, and length of stay-sex interaction. The observed vs predicted plot showed good fit. The estimated AUROC of 0.761 was robust in analyses that assessed sensitivity to a range of model assumptions. Our model has moderate power for identifying hospitalized Medicaid patients with diabetes who are at high risk of readmission. It is a template for identifying patients at risk of readmission and for adjusting comparisons of 30-day readmission rates among sites or over time.

Evaluating the performance of existing and novel equivalence tests for fit indices in structural equation modelling.

It has been suggested that equivalence testing (otherwise known as negligible effect testing) should be used to evaluate model fit within structural equation modelling (SEM). In this study, we propose novel variations of equivalence tests based on the popular root mean squared error of approximation and comparative fit index fit indices. Using Monte Carlo simulations, we compare the performance of these novel tests to other existing equivalence testing-based fit indices in SEM, as well as to other methods commonly used to evaluate model fit. Results indicate that equivalence tests in SEM have good Type I error control and display considerable power for detecting well-fitting models in medium to large sample sizes. At small sample sizes, relative to traditional fit indices, equivalence tests limit the chance of supporting a poorly fitting model. We also present an illustrative example to demonstrate how equivalence tests may be incorporated in model fit reporting. Equivalence tests in SEM also have unique interpretational advantages compared to other methods of model fit evaluation. We recommend that equivalence tests be utilized in conjunction with descriptive fit indices to provide more evidence when evaluating model fit.

The Influence of Social Impact, and Product Quality on Sustainable Business Growth in the Textile Industry in Bandung

Within the framework of Bandung's textile industry, this study explores the intricate relationships that exist between social effect, product quality, and sustainable economic success. The survey included a sample of 150 companies with a range of product specializations and sizes. Using partial least squares structural equation modeling, measurement model assessment, discriminant validity analysis, and structural model analysis were carried out (PLS-SEM). Product quality, social impact, and sustainable business growth were found to be significantly positively correlated. The results also confirmed discriminant validity among the latent constructs and showed strong reliability and validity of the measurement model. The suggested structural equation model's applicability is highlighted by the model fit evaluation. It can be shown from the R-Square and Adjusted R-Square values that the model can account for almost half of the variation in sustainable business growth. Future research directions are suggested, and implications for corporations and policy makers are examined.

Validation of the children international IgA nephropathy prediction tool based on data in Southwest China.

Immunoglobulin A nephropathy (IgAN) is one of the most common kidney diseases leading to renal injury. Of pediatric cases, 25%-30% progress into end-stage kidney disease (ESKD) in 20-25 years. Therefore, predicting and intervening in IgAN at an early stage is crucial. The purpose of this study was to validate the availability of an international predictive tool for childhood IgAN in a cohort of children with IgAN treated at a regional medical centre. An external validation cohort of children with IgAN from medical centers in Southwest China was formed to validate the predictive performance of the two full models with and without race differences by comparing four measures: area under the curve (AUC), the regression coefficient of linear prediction (PI), survival analysis curves for different risk groups, and R2D. A total of 210 Chinese children, including 129 males, with an overall mean age of 9.43 ± 2.71 years, were incorporated from this regional medical center. In total, 11.43% (24/210) of patients achieved an outcome with a GFR decrease of more than 30% or reached ESKD. The AUC of the full model with race was 0.685 (95% CI: 0.570-0.800) and the AUC of the full model without race was 0.640 (95% CI: 0.517-0.764). The PI of the full model with race and without race was 0.816 (SE = 0.006, P < 0.001) and 0.751 (SE = 0.005, P < 0.001), respectively. The results of the survival curve analysis suggested the two models could not well distinguish between the low-risk and high-risk groups (P = 0.359 and P = 0.452), respectively, no matter the race difference. The evaluation of model fit for the full model with race was 66.5% and without race was 56.2%. The international IgAN prediction tool has risk factors chosen based on adult data, and the validation cohort did not fully align with the derivation cohort in terms of demographic characteristics, clinical baseline levels, and pathological presentation, so the tool may not be highly applicable to children. We need to build IgAN prediction models that are more applicable to Chinese children based on their particular data.

A Study on the Impact of the Usage of Cost Information on Business Performance of Enterprises in Vietnam

Purpose: The primary objective of the research was to investigate the correlation between the utilization of cost information and business performance of enterprises in Vietnam, particularly in the context of the Covid-19 pandemic. Design/methodology/approach: A survey was conducted, involving a sample of 380 participants consisting of CEOs, CFOs, managers, board of directors, and individuals in charge of accounting and finance departments. The study employed a structure equation model to analyze the relationship between the use of cost information and business performance. Findings: The study revealed a significant and positive impact of cost information utilization on business performance among the surveyed enterprises in Vietnam. Additionally, the study provided recommendations for enterprises in Vietnam on how to make use of cost information for various purposes, including planning, evaluating, decision-making, and cost control, to optimize their business performance. Research, Practical &amp; Social implication: The study's results suggest that utilizing cost information effectively can lead to improved business performance and may provide valuable insights for Vietnamese enterprises on how to navigate the challenging and competitive post-Covid-19 economic environment. Originality/value: The research employed a structural equation modeling (SEM) approach, and a test for univariate normality demonstrated an outstanding critical skewness ratio value. Furthermore, the kurtosis indicated that the data followed a normal distribution, making it suitable for analysis. Since SEM employs rigorous criteria to evaluate model fit, it can be inferred that the measurement model exhibited a high level of fit. The findings affirm the beneficial impact of utilizing cost information on business performance and offer significant recommendations for Vietnamese businesses in the current post-COVID era.

Validation of the Rainbow Model of Integrated Care Measurement Tool in Parkinson's Disease.

Integrated care is essential for improving the management and health outcomes for people with Parkinson's disease (PD); reliable and objective measures of care integration are few. The aim of this study was to test the psychometric properties of the Rainbow Model of Integrated Care Measurement Tool (RMIC-MT, provider version) for healthcare professionals involved in PD care. A cross-sectional survey was administered online to an international network representing 95 neurology centers across 41 countries and 588 healthcare providers. Exploratory factor analysis with principal axis extraction method was used to assess construct validity. Confirmatory factor analysis was used to evaluate model fit of the RMIC-MT provider version. Cronbach's alpha was used to assess the internal consistency reliability. Overall, 371 care providers (62% response rate) participated in this study. No item had psychometric sensitivity problems. Nine factors (professional coordination, cultural competence, triple aims outcome, system coordination, clinical coordination, technical competence, community-centeredness, person-centeredness, and organizational coordination) with 42 items were determined by exploratory factor analysis. Cronbach's alpha ranged from 0.76 (clinical coordination) to 0.94 (system coordination) and showed significant correlation among all items in the scale (>0.4), indicating good internal consistency reliability. The confirmatory factor analysis model passed most goodness-of-fit tests, thereby confirming the factor structure of nine categories with a total of 40 items. The results provide evidence for the construct validity and other psychometric properties of the provider version of the RMIC-MT to measure integrated care in PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The effects of timing onset and progression of AKI on the clinical outcomes in AKI patients with sepsis: a prospective multicenter cohort study

Background Limited studies are available concerning on the earlier identification of AKI with sepsis. The aim of the study was to identify the risk factors of AKI early which depended on the timing onset and progression of AKI and investigate the effects of timing onset and progression of AKI on clinical outcomes. Methods Patients who developed sepsis during their first 48-h admission to ICU were included. The primary outcome was major adverse kidney events (MAKE) consisted of all-cause mortality, RRT-dependence, or an inability to recover to 1.5 times of the baseline creatinine value up to 30 days. We determined MAKE and in-hospital mortality by multivariable logistic regression and explored the risk factors of early persistent-AKI. C statistics were used to evaluate model fit. Results 58.7% sepsis patients developed AKI. According to the timing onset and progression of AKI, Early transient-AKI, early persistent-AKI, late transient-AKI, late persistent-AKI were identified. Clinical outcomes were quite different among subgroups. Early persistent-AKI had 3.0-fold (OR 3.04, 95% CI 1.61 − 4.62) risk of MAKE and 2.6-fold (OR 2.60, 95%CI 1.72 − 3.76) risk of in-hospital mortality increased compared with the late transients-AKI. Older age, underweight, obese, faster heart rate, lower MAP, platelet, hematocrit, pH and energy intake during the first 24 h on ICU admission could well predict the early persistent-AKI in patients with sepsis. Conclusion Four AKI subphenotypes were identified based on the timing onset and progression of AKI. Early persistent-AKI showed higher risk of major adverse kidney events and in-hospital mortality. Trial registration This study was registered in the Chinese Clinical Trials Registry (www.chictr.org/cn) under registration number ChiCTR-ECH-13003934.

Evaluating Model Fit of Measurement Models in Confirmatory Factor Analysis.

Confirmatory factor analyses (CFA) are often used in psychological research when developing measurement models for psychological constructs. Evaluating CFA model fit can be quite challenging, as tests for exact model fit may focus on negligible deviances, while fit indices cannot be interpreted absolutely without specifying thresholds or cutoffs. In this study, we review how model fit in CFA is evaluated in psychological research using fit indices and compare the reported values with established cutoff rules. For this, we collected data on all CFA models in Psychological Assessment from the years 2015 to 2020 . In addition, we reevaluate model fit with newly developed methods that derive fit index cutoffs that are tailored to the respective measurement model and the data characteristics at hand. The results of our review indicate that the model fit in many studies has to be seen critically, especially with regard to the usually imposed independent clusters constraints. In addition, many studies do not fully report all results that are necessary to re-evaluate model fit. We discuss these findings against new developments in model fit evaluation and methods for specification search.

Normative values for grip strength, gait speed, timed up and go, single leg balance, and chair rise derived from the Canadian longitudinal study on ageing.

decreased muscle strength and physical function often precede disability, nursing home admission, home care use and mortality in older adults. Normative values for commonly used physical performance-based tests are not widely available for older adults but are required for clinicians and researchers to easily identify individuals with low performance. to develop normative values for grip strength, gait speed, timed up and go, single-leg balance and five-repetition chair rise tests in a large population-based sample of Canadians aged 45-85years. baseline data (2011-2015) from the Canadian Longitudinal Study on Ageing was used to estimate age- and sex-specific normative values for each of the physical tests. Participants were without disability or mobility limitation (no assistance with activities of daily living or use of mobility devices). of the 25,470 participants eligible for the analyses 48.6% (n = 12,369) were female with a mean age of 58.6 ± 9.5years. Sex-specific 5th, 10th, 20th, 50th, 80th, 90th and 95th percentile values for each physical performance-based test were estimated. Cross-validation (n = 100 repetitions) with a 30% holdout sample was used to evaluate model fit. the normative values developed in this paper can be used in clinical and research settings to identify individuals with low performance relative to their peers of the same age and sex. Interventions targeting these at-risk individuals including physical activity can prevent or delay mobility disability and the resulting cascade of increasing care requirements, health care costs and mortality.

Pooling test statistics across multiply imputed datasets for nonnormal items.

In structural equation modeling, when multiple imputation is used for handling missing data, model fit evaluation involves pooling likelihood-ratio test statistics across imputations. Under the normality assumption, the two most popular pooling approaches were proposed by Li et al. (Statistica Sinica, 1(1), 65-92, 1991) and Meng and Rubin (Biometrika, 79(1), 103-111, 1992). When the assumption of normality is violated, it is not clear how well these pooling approaches work with the test statistics generated from various robust estimators and multiple imputation methods. Jorgensen and colleagues (2021) implemented these pooling approaches in their R package semTools; however, no systematical evaluation has been conducted. In this simulation study, we examine the performance of these approaches in working with different imputation methods and robust estimators under nonnormality. We found that the naïve pooling approach based on Meng and Rubin (Biometrika, 79(1), 103-111, 1992; D3SN) worked the best when combining with the normal-theory-based imputation and either MLM or MLMV estimator.

Are There Distinct Cardiovascular Subclasses in Acute Respiratory Distress Syndrome? Maybe.

Are There Distinct Cardiovascular Subclasses in Acute Respiratory Distress Syndrome? Maybe.

Early labour experience and labour characteristics after introduction of an electronic early labour educational intervention

ObjectiveThe study’s aim was to compare first-time mothers’ experience of early labour and subsequent labour characteristics before and after introducing an online early labour educational intervention. This article also reports on further testing of the underlying structure of the of the Early Labour Experience Questionnaire (ELEQ) in a Norwegian setting. MethodsPre- and post-intervention cohorts were recruited. The ELEQ was translated into Norwegian, back-translated and distributed among primiparous mothers whilst in hospital. Confirmatory factor analyses were used to evaluate model fit, and the internal consistency of the scale was measured by Cronbach’s α coefficient. The relationship between cohorts and demographic characteristics were analysed using chi-square statistics and t-tests. ResultsConfirmatory factor analysis of the Swedish version of the ELEQ for primiparous women showed an acceptable fit. Neither the overall score nor the scores on the subscales for emotional well-being, emotional distress and perceptions of midwifery care differed significantly, but there was a significant difference between the groups on a few of the items. The cervix was significantly more dilated upon admission in the post-intervention group, and oxytocin use was significantly reduced. The number of telephone consultations increased significantly after the intervention was introduced. ConclusionThe intervention did not improve women’s experience with early labour. However, women who received the intervention were admitted in more advanced labour and required less oxytocin. The increased number of telephone consultations may indicate that an online early labour educational programme cannot replace women’s need to communicate directly with staff.