Equivalence Testing for Factor Invariance Assessment with Categorical Indicators

2019 ◽  
pp. 229-242
Author(s):  
W. Holmes Finch ◽  
Brian F. French
Keyword(s):  
Equivalence Testing ◽  
Factor Invariance

PrePrint - Exploring Perceptions of Meaningful Relationships

2018 ◽  
Author(s):  
Nataly Beribisky ◽  
Heather Davidson ◽  
Rob Cribbie
Keyword(s):  
Effect Size ◽  
Mean Difference ◽  
Practical Significance ◽  
Equivalence Testing ◽  
Significant Variability ◽  
Meaningful Relationship ◽  
Meaningful Relationships ◽  
Context Free

Researchers often need to consider the practical significance of a relationship. For example, interpreting the magnitude of an effect size or establishing bounds in equivalence testing requires knowledge of the meaningfulness of a relationship. However, there has been little research exploring the degree of relationship among variables (e.g., correlation, mean difference) necessary for an association to be interpreted as meaningful or practically significant. In this study, we presented statistically trained and untrained participants with a collection of figures that displayed varying degrees of mean difference between groups or correlations among variables and participants indicated whether or not each relationship was meaningful. The results suggest that statistically trained and untrained participants differ in their qualification of a meaningful relationship, and that there is significant variability in how large a relationship must be before it is labeled meaningful. The results also shed some light on what degree of relationship is considered meaningful by individuals in a context-free setting.

Comparing Intensive English Program (IEP) and Directly-Admitted International Students’ Academic Achievement

2020 ◽  
Author(s):  
Anthony Schmidt
Keyword(s):  
Higher Education ◽  
International Students ◽  
Equivalence Testing ◽  
Intensive English ◽  
Intensive English Program ◽  
Student Groups ◽  
First Semester ◽  
Intensive English Programs ◽  
Statistical Equivalence ◽  
Direct Admission

Intensive English programs (IEPs) exist as an additional pathway into higher education for international students who need additional language support before full matriculation. Despite their long history in higher education, there is little research on the effectiveness of these programs. The current research examines the effectiveness of an IEP by comparing IEP students to directly-admitted international students. Results from regression models on first-semester and first-year GPA indicated no significant differences between these two student groups. Follow-up equivalence testing indicated statistical equivalence in several cases. The findings lead to the conclusion that the IEP is effective in helping students perform on par with directly-admitted international students. These findings imply further support for IEPs and alterative pathways to direct admission.

scholarly journals Equivalence Testing for Regression Discontinuity Designs

2020 ◽  
pp. 1-17
Author(s):  
Erin Hartman
Keyword(s):  
Political Science ◽  
Current Practice ◽  
Regression Discontinuity ◽  
Regression Function ◽  
Superior Performance ◽  
Equivalence Testing ◽  
Simulation Studies ◽  
Equivalence Tests ◽  
Regression Discontinuity Designs ◽  
Testing Approach

Abstract Regression discontinuity (RD) designs are increasingly common in political science. They have many advantages, including a known and observable treatment assignment mechanism. The literature has emphasized the need for “falsification tests” and ways to assess the validity of the design. When implementing RD designs, researchers typically rely on two falsification tests, based on empirically testable implications of the identifying assumptions, to argue the design is credible. These tests, one for continuity in the regression function for a pretreatment covariate, and one for continuity in the density of the forcing variable, use a null of no difference in the parameter of interest at the discontinuity. Common practice can, incorrectly, conflate a failure to reject evidence of a flawed design with evidence that the design is credible. The well-known equivalence testing approach addresses these problems, but how to implement equivalence tests in the RD framework is not straightforward. This paper develops two equivalence tests tailored for RD designs that allow researchers to provide statistical evidence that the design is credible. Simulation studies show the superior performance of equivalence-based tests over tests-of-difference, as used in current practice. The tests are applied to the close elections RD data presented in Eggers et al. (2015b).

Strategy to equivalence testing for development and scale up of biopharmaceutical downstream processes

2021 ◽  
Vol 235 ◽  
pp. 116497
Author(s):  
Christina Yassouridis ◽  
Astrid Dürauer ◽  
Theresa Scharl ◽  
Friedrich Leisch ◽  
Cécile Brocard ◽  
...  
Keyword(s):  
Scale Up ◽  
Equivalence Testing ◽  
Downstream Processes

scholarly journals MET: a Java package for fast molecule equivalence testing

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Jördis-Ann Schüler ◽  
Steffen Rechner ◽  
Matthias Müller-Hannemann
Keyword(s):  
Chemical Properties ◽  
Graph Isomorphism ◽  
Isomorphism Problem ◽  
Equivalence Classes ◽  
Equivalence Testing ◽  
Equivalence Test ◽  
Graph Isomorphism Problem ◽  
2D Structure ◽  
Node Labels ◽  
Labelled Graphs

AbstractAn important task in cheminformatics is to test whether two molecules are equivalent with respect to their 2D structure. Mathematically, this amounts to solving the graph isomorphism problem for labelled graphs. In this paper, we present an approach which exploits chemical properties and the local neighbourhood of atoms to define highly distinctive node labels. These characteristic labels are the key for clever partitioning molecules into molecule equivalence classes and an effective equivalence test. Based on extensive computational experiments, we show that our algorithm is significantly faster than existing implementations within , and . We provide our Java implementation as an easy-to-use, open-source package (via GitHub) which is compatible with . It fully supports the distinction of different isotopes and molecules with radicals.

Measurement Invariant but Non-Normal Treatment Responses in Guided Internet Psychotherapies for Depressive and Generalized Anxiety Disorders

Assessment ◽  
2021 ◽  
pp. 107319112110625
Author(s):  
Tom H. Rosenström ◽  
Ville Ritola ◽  
Suoma Saarni ◽  
Grigori Joffe ◽  
Jan-Henry Stenberg
Keyword(s):  
Anxiety Disorder ◽  
Treatment Response ◽  
Generalized Anxiety Disorder ◽  
Health Assessment ◽  
Psychotherapy Research ◽  
Self Report ◽  
Generalized Anxiety ◽  
Equivalence Testing ◽  
Sum Scores ◽  
Normally Distributed

Assessment of treatment response in psychotherapies can be undermined by lack of longitudinal measurement invariance (LMI) in symptom self-report inventories, by measurement error, and/or by wrong model assumptions. To understand and compare these threats to validity of outcome assessment in psychotherapy research, we studied LMI, sum scores, and Davidian Curve Item Response Theory models in a naturalistic guided internet psychotherapy treatment register of 2,218 generalized anxiety disorder (GAD) patients and 3,922 depressive disorder (DD) patients (aged ≥16 years). Symptoms were repeatedly assessed by Generalized Anxiety Disorder Assessment-7 (GAD-7) or Beck Depression Inventory. The symptom self-reports adhered to LMI under equivalence testing, suggesting sum scores are reasonable proxies for disorder status. However, the standard LMI assumption of normally distributed latent factors did not hold and inflated treatment response estimates by 0.2 to 0.3 standard deviation units compared with sum scores. Further methodological research on non-normally distributed latent constructs holds promise in advancing LMI and mental health assessment.

Measurement equivalence testing of the American Identity Questionnaire across Black, Latino, and White adolescents.

2021 ◽  
Author(s):  
Stefanie Martinez-Fuentes ◽  
Adriana J. Umaña-Taylor ◽  
Justin Jager ◽  
Elana R. McDermott ◽  
Michael R. Sladek
Keyword(s):  
Measurement Equivalence ◽  
American Identity ◽  
White Adolescents ◽  
Equivalence Testing

Choice of Delta in Equivalence Testing

2001 ◽  
Vol 35 (4) ◽  
pp. 1517-1527 ◽  
Author(s):  
Tie-Hua Ng
Keyword(s):  
Equivalence Testing

THE ELEMENTARY READING ATTITUDE SURVEY: FACTOR INVARIANCE ACROSS GENDER AND RACE

2004 ◽  
Vol 25 (2) ◽  
pp. 111-120 ◽  
Author(s):  
RICHARD KAZELSKIS ◽  
DANA THAMES ◽  
CAROLYN REEVES
Keyword(s):  
Elementary Reading ◽  
Reading Attitude ◽  
Attitude Survey ◽  
Gender And Race ◽  
Factor Invariance
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