scholarly journals Detecting Instruction Effects—Deciding Between Covariance Analytical and Change-Score Approach

2021 ◽  
Author(s):  
Carmen Köhler ◽  
Johannes Hartig ◽  
Alexander Naumann
Keyword(s):  
Latent Variable ◽  
Outcome Measurement ◽  
Predictor Variable ◽  
Change Score ◽  
Regression Coefficients ◽  
Outcome Variable ◽  
Analysis Model ◽  
Hypothetical Data ◽  
Instructional Research ◽  
Time Point

AbstractThe article focuses on estimating effects in nonrandomized studies with two outcome measurement occasions and one predictor variable. Given such a design, the analysis approach can be to include the measurement at the previous time point as a predictor in the regression model (ANCOVA), or to predict the change-score of the outcome variable (CHANGE). Researchers demonstrated that both approaches can result in different conclusions regarding the reported effect. Current recommendations on when to apply which approach are, in part, contradictory. In addition, they lack direct reference to the educational and instructional research contexts, since they do not consider latent variable models in which variables are measured without measurement error. This contribution assists researchers in making decisions regarding their analysis model. Using an underlying hypothetical data-generating model, we identify for which kind of data-generating scenario (i.e., under which assumptions) the defined true effect equals the estimated regression coefficients of the ANCOVA and the CHANGE approach. We give empirical examples from instructional research and discuss which approach is more appropriate, respectively.

scholarly journals Does Exposure to High Job Demands, Low Decision Authority, or Workplace Violence Mediate the Association between Employment in the Health and Social Care Industry and Register-Based Sickness Absence? A Longitudinal Study of a Swedish Cohort

2021 ◽  
Vol 19 (1) ◽  
pp. 53
Author(s):  
Anna Nyberg ◽  
Paraskevi Peristera ◽  
Susanna Toivanen ◽  
Gun Johansson
Keyword(s):  
Sickness Absence ◽  
Workplace Violence ◽  
Social Care ◽  
Predictor Variable ◽  
Job Demands ◽  
Outcome Variable ◽  
Care Industry ◽  
Decision Authority ◽  
Health And Social Care ◽  
Time Point

Background: The aim of this paper was to investigate if job demands, decision authority, and workplace violence mediate the association between employment in the health and social care industry and register-based sickness absence. Methods: Participants from the Swedish Longitudinal Occupational Survey of Health who responded to questionnaires in 2006–2016 (n = 3951) were included. Multilevel autoregressive cross-lagged mediation models were fitted to the data. Employment in the health and social care industry at one time point was used as the predictor variable and register-based sickness absence >14 days as the outcome variable. Self-reported levels of job demands, decision authority, and exposure to workplace violence from the first time point were used as mediating variables. Results: The direct path between employment in the health and social care industry and sickness absence >14 days was, while adjusting for the reverse path, 0.032, p = 0.002. The indirect effect mediated by low decision authority was 0.002, p = 0.006 and the one mediated by exposure to workplace violence was 0.008, p = 0.002. High job demands were not found to mediate the association. Conclusion: Workplace violence and low decision authority may, to a small extent, mediate the association between employment in the health and social care industry and sickness absence.

The Most Dangerous Game: A Review of Head and Neck Injuries in American Football and Rugby

2022 ◽  
pp. 194338752110734
Author(s):  
Jordan Richardson ◽  
Dani Stanbouly ◽  
Harrison Moynihan ◽  
Renée M. Reynolds ◽  
Matthew J. Recker ◽  
...  
Keyword(s):  
Emergency Department ◽  
Hospital Admission ◽  
Head And Neck ◽  
Predictor Variable ◽  
American Football ◽  
Outcome Variable ◽  
Neck Injuries ◽  
Injury Surveillance System ◽  
Admission Rates ◽  
Increased Risk

Study Design The investigators designed and implemented a 20-year cross-sectional study using the National Electronic Injury Surveillance System database. Objective The purpose of this study is to estimate and compare hospital admission (danger) rates between rugby and football of those who presented to the emergency department with head and neck injuries after playing these sports. Methods The primary predictor variable was sport played. The primary outcome variable was danger, measured by hospital admission rates. Results Over the past 20 years, there has been a trend of decreasing incidence of injuries presenting to the emergency department in both sports. There was no difference in the rate of hospital admission when comparing football and rugby (OR, 1.2; P = .1). Male gender was associated with an increased risk of admission. Other variables associated with hospital admission included white racial group, injury taking place in the fall, being either young (15–24 years old) or senior (65 years of age and over), and being injured at school or at a sport/recreational facility. Conclusions There is no difference in danger as measured by admission rates between American football and rugby. There exists, however, several variables that are associated with admission when sustaining injury to the head and neck, when playing these two sports.

scholarly journals Stronger Association between Nucleus Accumbens Density and Body Mass Index in Low-Income and African American Children

2020 ◽  
Vol 5 (2) ◽  
pp. p107
Author(s):  
Shervin Assari
Keyword(s):  
Body Mass Index ◽  
African American ◽  
Nucleus Accumbens ◽  
Body Mass ◽  
Low Income ◽  
Parental Education ◽  
Predictor Variable ◽  
Outcome Variable ◽  
Ses Differences

Background: The nucleus accumbens’ (NAc) size, function, and density influence individuals’ body mass index (BMI). However, little is known about racial and socioeconomic status (SES) differences in the role of NAc density as a predictor of childhood BMI. Objectives: We used the Adolescent Brain Cognitive Development (ABCD) data to investigate racial and SES differences in the effect of NAc density on childhood BMI. Methods: This cross-sectional study included 9497 children between ages 9 and 10. Mixed-effects regression models were used to analyze the data. The predictor variable was NAc density measured using diffusion MRI (dMRI). The outcome variable was BMI, operationalized as a continuous variable. Covariates included sex, age, ethnicity, family structure, and parental education. Race (White, African American, Asian, and Other/mixed) and household income (< 50k, 50-100 k, and 100+ k) were the moderators. Results: High NAc diffusion tension (density) was predictive of higher BMI, net of covariates. However, the positive association between NAc density and BMI was stronger in African Americans than in White, and in low-income than in high-income children. Conclusions: Our findings suggest that although high NAc has implications for children’s BMI, this effect varies across racial and SES groups. More research should be performed on the role of obesogenic environments in altering the effect of NAc on childhood BMI.

Bayesian Adaptive Lasso for Ordinal Regression With Latent Variables

2015 ◽  
Vol 46 (4) ◽  
pp. 926-953 ◽  
Author(s):  
Xiang-Nan Feng ◽  
Hao-Tian Wu ◽  
Xin-Yuan Song
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Social Research ◽  
Ordinal Regression ◽  
Adaptive Lasso ◽  
Simultaneous Estimation ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
Explanatory Variables ◽  
Ordinal Regression Model

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct simultaneous estimation and variable selection. Nice features including empirical performance of the proposed methodology are demonstrated by simulation studies. The model is applied to a study on happiness and its potential determinants from the Inter-university Consortium for Political and Social Research.

scholarly journals Predicting Language Outcomes for Children Learning Augmentative and Alternative Communication: Child and Environmental Factors

2013 ◽  
Vol 56 (5) ◽  
pp. 1595-1612 ◽  
Author(s):  
Nancy C. Brady ◽  
Kathy Thiemann-Bourque ◽  
Kandace Fleming ◽  
Kris Matthews
Keyword(s):  
Augmentative And Alternative Communication ◽  
Latent Variable ◽  
Structural Equation ◽  
Communication Complexity ◽  
Equation Model ◽  
Preschool Age ◽  
Outcome Variable ◽  
Alternative Communication ◽  
Outcomes For Children ◽  
At Home

Purpose To investigate a model of language development for nonverbal preschool-age children learning to communicate with augmentative or alternative communication. Method Ninety-three preschool children with intellectual disabilities were assessed at Time 1, and 82 of these children were assessed 1 year later, at Time 2. The outcome variable was the number of different words the children produced (with speech, sign, or speech-generating devices). Children's intrinsic predictor for language was modeled as a latent variable consisting of cognitive development, comprehension, play, and nonverbal communication complexity. Adult input at school and home, and amount of augmentative or alternative communication instruction, were proposed mediators of vocabulary acquisition. Results A confirmatory factor analysis revealed that measures converged as a coherent construct, and a structural equation model indicated that the intrinsic child predictor construct predicted different words children produced. The amount of input received at home, but not at school, was a significant mediator. Conclusions The hypothesized model accurately reflects a latent construct of Intrinsic Symbolic Factor (ISF). Children who evidenced higher initial levels of ISF and more adult input at home produced more words 1 year later. The findings support the need to assess multiple child variables and suggest interventions directed to the indicators of ISF and input.

scholarly journals Efficacy of Combined Antigravity Treadmill and Conventional Rehabilitation After Hip Fracture in Patients With Sarcopenia

2020 ◽  
Vol 75 (10) ◽  
pp. e173-e181 ◽  
Author(s):  
Min-Kyun Oh ◽  
Jun-Il Yoo ◽  
Hayoung Byun ◽  
Se-Woong Chun ◽  
Seung-Kyu Lim ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Outcome Measurement ◽  
Change Score ◽  
Berg Balance Scale ◽  
Control Group ◽  
Walking Ability ◽  
Life Questionnaire ◽  
Long Term Effects ◽  
Change Scores ◽  
Korean Version

Abstract Background To compare long-term effects of antigravity treadmill (AGT) combined with conventional rehabilitation (CR) and CR after hip fracture in patients with sarcopenia. Methods Forty-five patients were randomly allocated to AGT combined with CR (experimental group) or CR (control group) for 10 consecutive working days. Participants were evaluated prior to treatment, 3 weeks, 3 months, and 6 months after treatment. Outcome measurement included Koval walking ability scores functional ambulatory category (FAC), Berg Balance Scale (BBS), Korean version of Mini-Mental State Examination, Euro Quality of Life Questionnaire Five-Dimensional Classification, Korean version of modified Barthel index, and grip strength. Results At 3 weeks and 3 months, the comparison of change scores in KOVAL between two groups revealed difference of 0.84 (95% CI: −1.19, −0.49; p for trend = .000) and 1.21 (95% CI: −2.05, −0.36; p for trend = .006), respectively. At 3 weeks, comparison of change score in FAC between two groups revealed a difference of 0.73 (95% CI: 0.28, 1.19; p for trend = .003). The comparison of change scores between two groups also showed a difference in the 6 months in KOVAL and in the 3 and 6 months in FAC. The comparison of changes in scores in BBS between two groups revealed difference of 11.63 (95% CI: 5.85, 17.40; p for trend = .001), 9.00 (95% CI: 2.28, 15.71; p for trend = .006), and 11.05 (95% CI: 3.62, 18.48; p for trend = .006), respectively, at each follow-up. Conclusions Both groups were improved after intervention. As additional benefits were evident among those who carried out AGT, it may be appropriate for patients with sarcopenia after hip fracture surgery.

scholarly journals A Review of Structural Equation Model for Construction Delay Study

2018 ◽  
Vol 7 (4.35) ◽  
pp. 299 ◽  
Author(s):  
Mohd Zakwan Ramli ◽  
Marlinda Abdul Malek ◽  
Mohamad Zaki Muda ◽  
Zulkhairi Abd Talib ◽  
Nor Syahirah Azman ◽  
...  
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
First Generation ◽  
Complex Analysis ◽  
Structural Model ◽  
Hidden Variables ◽  
Analysis Tool ◽  
Error Measurement ◽  
Analysis Model ◽  
Construction Delay

Structural Equation Modelling (SEM) has been widely used in science social area compared to construction engineering and management field especially in area of delay construction. SEM is a second generation multivariate analysis that has an advance features compare to first generations of analysis tools. First generation techniques suffer with some assumptions such as error measurement is neglected, only observed variable allowed, only for simple model and other limitations. In construction delay study, comprehensive and complex analysis which involves hidden variables need to be considered to get precise results. Therefore, the main objective of this paper is to review the importance of applying SEM for construction delay study. Various papers which were taken from construction delay and construction management studies has been reviewed to observe the suitability of SEM for construction delay study. Outcome of this review reveals that SEM can include latent variable in the analysis model and consider of error measurement as integral part of the model as well as simultaneously analyse theory and measurement in a structural model while it is unobtainable for first generation techniques.  This review proves that SEM can be an appropriate analysis tool for construction delay study.

Interpretation of regression coefficients under a latent variable regression model

2001 ◽  
Vol 15 (4) ◽  
pp. 265-284 ◽  
Author(s):  
Alison J. Burnham ◽  
John F. MacGregor ◽  
Roman Viveros
Keyword(s):  
Regression Model ◽  
Latent Variable ◽  
Regression Coefficients ◽  
Latent Variable Regression

Prediction to Successful Treatment Outcome by Client Characteristics and Retention in Treatment in Adolescent Drug Treatment Programs: A Large-Scale Cross Validation Study

1986 ◽  
Vol 16 (2) ◽  
pp. 149-165 ◽  
Author(s):  
Alfred S. Friedman ◽  
Nita W. Glickman ◽  
Margaret R. Morrissey
Keyword(s):  
Drug Use ◽  
Large Scale ◽  
Treatment Time ◽  
Predictor Variable ◽  
Treatment Programs ◽  
Outcome Variable ◽  
Client Characteristics ◽  
Successful Treatment Outcome ◽  
Time In Treatment ◽  
Retention In Treatment

NIDA–CODAP file data on adolescent clients admitted to thirty selected outpatient programs were available for calendar years 1979 ( N = 2509) and 1980 ( N = 3094). Two outcome criterion variables were utilized: 1) CODAP's “Reasons for Discharge” classification, and 2) a formula for “Reduction of Drug Use.” School grade, controlled for age, was the only client predictor variable found to account for more than 1 percent of the variance in the “Reasons for Discharge” outcome variable. Marijuana as the primary drug of abuse was the only client variable to account for more than 1 percent (4.4 percent) of the variance in the Reduction in Drug Use. The primary marijuana users showed less reduction in amount of drug use, and were less often considered to have completed the course of treatment. Time in treatment accounted for 1.6 percent in 1979 and 1.3 percent in 1980 of the variance in the “Reduction in Drug Use” criterion.

scholarly journals The Role of Virtual Surgical Planning in Increasing the Predictability in Orthognathic Surgery

2019 ◽  
pp. 136-141
Author(s):  
Faisal A Quereshy ◽  
Nikolay Levintov ◽  
Justin L Nguyen ◽  
Maria A DeLeonibus ◽  
Catherine Demko ◽  
...  
Keyword(s):  
Surgical Outcomes ◽  
Orthognathic Surgery ◽  
Surgical Planning ◽  
Predictor Variable ◽  
Outcome Variable ◽  
Virtual Surgical Planning ◽  
Equal Variance ◽  
Modeling Software ◽  
Cad Cam ◽  
Medical Modeling

Purpose: To evaluate our surgical outcomes by comparing our surgical plan to the outcome of the surgery and evaluate our efficacy using Virtual Surgical Planning and Medical Modeling software. Our aim is to determine the quality and validity of Virtual Surgical Planning when comparing pre-surgical plans with post-surgical outcomes. Patients and Methods: A cohort study was conducted for patients who underwent orthognathic surgery at a single institution.  Utilizing virtual plans and models, select points for the virtual plans were compared and superimposed with that of the actual surgical movements.  The primary predictor variable were the pre-surgical virtual plans of movements; the outcome variable consisted of the actual post-surgical movements.  Statistical analysis was computed via IBM SPSS Version 25 software utilizing a paired t-test assuming equal variance with alpha (p<0.05). The sample of patients included those who had pre-operative and post-operative cone beam computed tomography scans, a virtual surgical plan, CAD/CAM splints, and LeFort I osteotomy and bilateral sagittal split osteotomy.Results: The study consisted of ten patients between the ages of 18-51 years old. Pre and post surgical plans were superimposed and four points of measurement were compared along 3 dimensional planes. There were no statistical significant associations between the virtually planned and post surgical planned values.Conclusion: Our results suggest that the use of virtual surgical planning in orthognathic surgery yields favorable and accurate surgical outcomes regarding rotational movements with minor degrees of discrepancies.

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