Ordinal Approaches to Decomposing Between-Group Test Score Disparities

2020 ◽  
pp. 107699862096772
Author(s):  
David M. Quinn ◽  
Andrew D. Ho
Keyword(s):  
Test Score ◽  
Educational Inequality ◽  
Decomposition Methods ◽  
Ordered Probit ◽  
Group Differences ◽  
Scale Invariant ◽  
Gap Statistic ◽  
The Difference ◽  
Ordered Probit Models ◽  
Test Score Gaps

The estimation of test score “gaps” and gap trends plays an important role in monitoring educational inequality. Researchers decompose gaps and gap changes into within- and between-school portions to generate evidence on the role schools play in shaping these inequalities. However, existing decomposition methods assume an equal-interval test scale and are a poor fit to coarsened data such as proficiency categories. This leaves many potential data sources ill-suited for decomposition applications. We develop two decomposition approaches that overcome these limitations: an extension of V, an ordinal gap statistic, and an extension of ordered probit models. Simulations show V decompositions have negligible bias with small within-school samples. Ordered probit decompositions have negligible bias with large within-school samples but more serious bias with small within-school samples. More broadly, our methods enable analysts to (1) decompose the difference between two groups on any ordinal outcome into portions within- and between some third categorical variable and (2) estimate scale-invariant between-group differences that adjust for a categorical covariate.

Using Heteroskedastic Ordered Probit Models to Recover Moments of Continuous Test Score Distributions From Coarsened Data

2016 ◽  
Vol 42 (1) ◽  
pp. 3-45 ◽  
Author(s):  
Sean F. Reardon ◽  
Benjamin R. Shear ◽  
Katherine E. Castellano ◽  
Andrew D. Ho
Keyword(s):  
Test Score ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Ordered Probit ◽  
Parameter Estimates ◽  
Demographic Groups ◽  
Continuous Test ◽  
Standard Deviations ◽  
Ordered Probit Models ◽  
Score Distributions

Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups’ test score distributions from such data. Because the scale of HETOP estimates is indeterminate up to a linear transformation, we develop formulas for converting the HETOP parameter estimates and their standard errors to a scale in which the population distribution of scores is standardized. We demonstrate and evaluate this novel application of the HETOP model with a simulation study and using real test score data from two sources. We find that the HETOP model produces unbiased estimates of group means and standard deviations, except when group sample sizes are small. In such cases, we demonstrate that a “partially heteroskedastic” ordered probit (PHOP) model can produce estimates with a smaller root mean squared error than the fully heteroskedastic model.

Using Pooled Heteroskedastic Ordered Probit Models to Improve Small-Sample Estimates of Latent Test Score Distributions

2020 ◽  
pp. 107699862092291
Author(s):  
Benjamin R. Shear ◽  
Sean F. Reardon
Keyword(s):  
Test Score ◽  
Sampling Error ◽  
Small Sample ◽  
Ordered Probit ◽  
Sample Sizes ◽  
Ordered Categorical Data ◽  
Ordered Probit Models ◽  
Ordered Categorical ◽  
Real Test ◽  
Score Distributions

This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in each of a small number of ordered “proficiency” levels. HETOP models can be used to estimate means and standard deviations of the underlying (latent) test score distributions but may yield biased or very imprecise estimates when group sample sizes are small. A simulation study demonstrates that the pooled HETOP models described here can reduce the bias and sampling error of standard deviation estimates when group sample sizes are small. Analyses of real test score data demonstrate the use of the models and suggest the pooled models are likely to improve estimates in applied contexts.

scholarly journals An Analysis of Consumer Preferences for Value-Added Seafood Products Derived from Crawfish

2002 ◽  
Vol 31 (2) ◽  
pp. 157-170 ◽  
Author(s):  
R. Wes Harrison ◽  
Timothy Stringer ◽  
Witoon Prinyawiwatkul
Keyword(s):  
Conjoint Analysis ◽  
Consumer Preferences ◽  
Value Added ◽  
Utility Functions ◽  
Ordered Probit ◽  
Probit Models ◽  
Seafood Products ◽  
Ordered Probit Models ◽  
Old Men

Conjoint analysis is used to evaluate consumer preferences for three consumer-ready products derived from crawfish. Utility functions are estimated using two-limit tobit and ordered probit models. The results show women prefer a baked nugget or popper type product, whereas 35- to 44-year-old men prefer a microwavable nugget or patty type product. The results also show little difference between part-worth estimates or predicted rankings for the tobit and ordered probit models, implying the results are not sensitive to assumptions regarding the ordinal and cardinal nature of respondent preferences.

scholarly journals Case-based learning in integrated management of neonatal and childhood illness

2019 ◽  
Vol 6 (3) ◽  
pp. 1163
Author(s):  
Sundaram Kartikeyan ◽  
Aniruddha A. Malgaonkar
Keyword(s):  
Gender Differences ◽  
Test Scores ◽  
Test Score ◽  
Integrated Management ◽  
Childhood Illness ◽  
Cognitive Domain ◽  
Post Test ◽  
Case Based Learning ◽  
The Difference ◽  
Case Based

Background: This complete-enumeration, before-and-after type of study (without controls) was conducted on 61 third-year medical students at Rajiv Gandhi Medical College, Thane, Maharashtra state to study the difference in cognitive domain scores after attending lecture-based learning (by a pre-test) and after attending case-based learning (by a post-test).Methods: After approval from the institutional ethics committee, the purpose of the study was explained to third-year medical students and written informed consent was obtained. After curriculum-based lectures on integrated management of neonatal and childhood Illness, a pre-test was administered wherein each student was asked to fill up case sheets for five case scenarios. The maximum marks obtainable were 10 marks per case (total 50 marks).  Case-based learning was conducted in two sub-groups comprising 31 and 30 randomly assigned students by the same faculty and students in each sub-group were exposed to identical case scenarios. The post-test was conducted using case scenarios and case sheets that were identical to that of the pre-test.Results: The overall mean score increased and the difference between the case-wise pre-test and post-test scores of both female (n=35) and male (n=26) students was highly significant (p <0.00001). However, the gender differences in pre-test score (Z=1.038; p=0.299) and post-test score were not significant (Z=0.114; p=0.909).Conclusions: Using case scenarios augmented the cognitive domain scores of participating students and the gender differences in scores were not statistically significant. The post-test scores showed higher variability. Remedial educational interventions would be required for students who obtained low scores in the post-test.

scholarly journals Role of JIGSAW method of teaching in improving clinical diagnosis among final year medical students – A prospective observational study

2021 ◽  
Vol 12 (12) ◽  
pp. 44-49
Author(s):  
Appandraj S ◽  
Sivagamasundari V ◽  
Varatharajan Sakthivadivel
Keyword(s):  
Observational Study ◽  
Test Score ◽  
Prospective Observational Study ◽  
Coronary Syndrome ◽  
Post Test ◽  
Jigsaw Method ◽  
The Mean ◽  
The Difference ◽  
Didactic Lecture ◽  
Teaching Learning

Background: The Jigsaw method is a form of cooperative learning, in which students are actively involved in the teaching-learning process that improves the long-term retention of acquired knowledge. Aims and Objectives: The objective of this study was to assess the knowledge acquired by students using the Jigsaw learning method in Internal Medicine. Materials and Methods: A prospective observational study was conducted with 100 students. The acute coronary syndrome was taken for 1 h as a didactic lecture, and a pre-test was conducted. The students were divided into five groups and were put for the intervention “Jigsaw.” The pre- and post-test were conducted, and feedback was collected from the students. Paired t-test was used to perform analysis of pre- and post-test. Feedback evaluation was done by a 5-point Liker scale. P<0.05 was considered statistically significant, and the data were analyzed using CoGuide software. Results: The mean pre-test score was 8.44 ± 2.33 ranged (3–14) and the mean post-test score was 11.03 ± 2.07 (ranged 6–15). The difference of 2.39 (95% CI: 2.19–2.59) increase in marks post-test after the Jigsaw method was statistically significant (P<0.001). The satisfaction level was 50–55% on the Likert scale based on the questionnaire given. There was a significant improvement in the post-test scores of the students after Jigsaw. Conclusion: The Jigsaw method improved knowledge in the short-term by engaging students in group work and motivation to learn. Overall response based on the questionnaire about the Jigsaw method was positive.

scholarly journals Perbandingan Metode Pembelajaran Number Heads Together (NHT) Dan Metode Pembelajaran Student Team Achievement Division (STAD) Terhadap Hasil Belajar Siswa Kelas VII Di MTs Madinatussalam

2021 ◽  
Vol 9 (3) ◽  
pp. 195-201
Author(s):  
Adha Siagian ◽  
◽  
Kartika Manalu ◽  
Khairuddin Khairuddin
Keyword(s):  
Learning Outcomes ◽  
Test Score ◽  
Hypothesis Test ◽  
Class Ii ◽  
Class I ◽  
Choice Test ◽  
Learning Method ◽  
High Category ◽  
Post Test ◽  
The Difference

This study aims to determine the differences between NHT) and STAD learning outcomes of clas VII Biology MTs Madinatussalam. The sample of this research is class VII-1 with 32 student as NHT class and 32 student in VII-2 as STAD class. The instrument used in this study was a multiple choice test concisting of 20 questions. The results of analysis showed that the average post-test score for the experimental class I NHT was 82 very high category. Meanwhile, the experimental class II STAD the average post-test score was 67,2 high category. The hypothesis test of the difference in learning outcomes of students in expremental class I NHT and expremental class II STAD, obtained tcount = 6,036>ttable = 1.999, then Ho is rejected and Ha is acepted. This shows that there is a difference in the biology lerning out comes of student who are thought using NHT learning method and those taught using the STAD learning method.

Analysis of Wisc Coding: 2. Memory and Verbal Mediation

1972 ◽  
Vol 34 (2) ◽  
pp. 659-662 ◽  
Author(s):  
E. G. Johnson ◽  
J. G. Lyle
Keyword(s):  
Group Differences ◽  
Strategy Group ◽  
Verbal Mediation ◽  
The Difference

Investigations were carried out to determine whether the difference between good and poor coders of equal CA and IQ was accounted for by (a) differential recall of the symbols and associates and (b) by differential application of a labeling strategy. Group differences were found in recall. Training in labeling improved coding performance of both groups but not differentially.

Has Curriculum Closed the Test Score Gap in Math?

2004 ◽  
Vol 4 (1) ◽  
Author(s):  
Heather Rose
Keyword(s):  
High School ◽  
Test Score ◽  
Mathematics Curriculum ◽  
School Characteristics ◽  
National Education ◽  
Test Score Gap ◽  
National Education Longitudinal Study ◽  
White Test ◽  
Test Score Gaps ◽  
Hispanic White

Abstract This study examines the extent to which convergence in mathematics course-taking behavior is responsible for narrowing the Hispanic-white and the black-white test score gaps during the 1980s. Mathematics curriculum is measured in detail using high school transcript data from both High School and Beyond and the National Education Longitudinal Study of 1988. After controlling for demographic, family, and school characteristics, changes in curriculum account for about 60 percent of the narrowing Hispanic-white test score gap between 1982 and 1992. However, the black-white test score gap did not drop significantly.

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