Barbara G Dodd
Biographic Data
| ID | 5145787 |
|---|---|
| NAME | Barbara G Dodd |
| GIVEN NAMES | Barbara G |
| FAMILY NAME | Dodd |
| SIGNATURE | DODD B G |
| AFFILIATIONS | The University of Texas at Austin |
| VERIFIED | No |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 18 |
| AUTHOR COUNT | 14 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1991 |
| LATEST PUBLICATION YEAR | 2017 |
| H-INDEX | 1 |
The Development of MST Test Information for the Prediction of Test Performances
The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the validity of the proposed method in both measurement precision and classification accuracy. The resul…
The Impact of Varied Discrimination Parameters on Mixed-Format Item Response Theory Model Selection
Whittaker, Chang, and Dodd compared the performance of model selection criteria when selecting among mixed-format IRT models and found that the criteria did not perform adequately when selecting the more parameterized models. It was suggested by M. S. Johnson that the problems when selecting the more parameterized models may be because of the low variance of the discrimination parameters used to generate the data. This simulation study reproduced…
A Comparison of Exposure Control Procedures in CATs Using the 3PL Model
This study compares the progressive-restricted standard error (PR-SE) exposure control procedure to three commonly used procedures in computerized adaptive testing, the randomesque, Sympson–Hetter (SH), and no exposure control methods. The performance of these four procedures is evaluated using the three-parameter logistic model under the manipulated conditions of item pool size (small vs. large) and stopping rules (fixed-length vs. variable-leng…
Balancing Flexible Constraints and Measurement Precision in Computerized Adaptive Testing
Managing test specifications—both multiple nonstatistical constraints and flexibly defined constraints—has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT, and the weighted penalty model in balancing multiple flexible constraints and maximizing measurement prec…
Panel Design Variations in the Multistage Test Using the Mixed-Format Tests
This study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized adaptive test (CAT) conditions provided baseline comparisons. Three passing rate conditions were also …
Comparison of Exposure Controls, Item Pool Characteristics, and Population Distributions for CAT Using the Partial Credit Model
This study investigated item exposure control procedures under various combinations of item pool characteristics and ability distributions in computerized adaptive testing based on the partial credit model. Three variables were manipulated: item pool characteristics (120 items for each of easy, medium, and hard item pools), two ability distributions (normally distributed and negatively skewed data), and three exposure control procedures (randomes…
A New Stopping Rule for Computerized Adaptive Testing
The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared with that of the minimum standard error stopping rule and a modified version of the minimum in…
Exploring Asian American racial identity
In this study the authors used cluster analysis to create racial identity profiles for a sample of Asian Americans using the People of Color Racial Identity Attitudes Scale (PCRIAS). A four-cluster solution was chosen: each cluster corresponded to one PCRIAS subscale and was named accordingly. Scores on the Asian American Racism-Related Stress Inventory and the Color-Blind Racial Attitudes Scale were compared across clusters. As expected, the Dis…
A Comparison of Maximum Likelihood Estimation and Expected a Posteriori Estimation in CAT Using the Partial Credit Model
A simulation study was conducted to investigate the application of expected a posteriori (EAP) trait estimation in computerized adaptive tests (CAT) based on the partial credit model and compare it with maximum likelihood trait estimation (MLE). The performance of EAP was evaluated under different conditions: the number of quadrature points (10, 20,40, and 80) and the type of prior distribution (normal and uniform). The relative performance of ML…
The Effect of Population Distribution and Method of Theta Estimation on Computerized Adaptive Testing (CAT) Using the Rating Scale Model
A simulation study was conducted to investigate the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori estimation (EAP) in computerized adaptive testing (CAT) based on Andrich's rating scale model. Comparisons were made among MLE and EAP with a normal prior distribution and EAP with a uniform prior distribution within two data sets: one generated using a normal trait distribution and the other using…
An Investigation of Procedures for Computerized Adaptive Testing Using the Successive Intervals Rasch Model
The major objective of the present study was to evaluate basic procedures for performing computerized adaptive testing (CAT) based on the successive intervals (SI) Rasch model. The SI model is designed for measuring attitudes based on Thurstone's successive intervals concept. The SI model was applied to both simulated and real attitude data sets for which the item response data were polytomous. Using simulated data, such variables as item pool si…
Item and Scale Information Functions for the Successive Intervals Rasch Model
Simulated data were used to investigate systematically the impact of various characteristics of the threshold values (number, symmetry, and distance between adjacent threshold values) and of the delta values on the distribution of item information in the successive intervals Rasch model. The results revealed that the shift in the peak of the information function away from the scale value of an item depended on the degree of asymmetry of the thres…
Computerized Adaptive Testing Using the Partial Credit Model
Simulated datasets were used to research the effects of the systematic variation of three major variables on the performance of computerized adaptive testing (CAT) procedures for the partial credit model. The three variables studied were the stopping rule for terminating the CATs, item pool size, and the distribution of the difficulty of the items in the pool. Results indicated that the standard error stopping rule performed better across the var…
Partial Credit Analysis of Writing Ability
The direct assessment of the writing ability of 2000 randomly selected secondary school students was performed using the partial credit model. The effects on item parameter estimates of rating scale and type of writing sample were investigated. The rating scales used were a sum and an averaging of the individual raters' ratings and the types of items were expository and narrative. Results showed that expository items tended to provide more inform…
Exploring Asian American racial identity
In this study the authors used cluster analysis to create racial identity profiles for a sample of Asian Americans using the People of Color Racial Identity Attitudes Scale (PCRIAS). A four-cluster solution was chosen: each cluster corresponded to one PCRIAS subscale and was named accordingly. Scores on the Asian American Racism-Related Stress Inventory and the Color-Blind Racial Attitudes Scale were compared across clusters. As expected, the Dis…
Partial Credit Analysis of Writing Ability
The direct assessment of the writing ability of 2000 randomly selected secondary school students was performed using the partial credit model. The effects on item parameter estimates of rating scale and type of writing sample were investigated. The rating scales used were a sum and an averaging of the individual raters' ratings and the types of items were expository and narrative. Results showed that expository items tended to provide more inform…
Computerized Adaptive Testing Using the Partial Credit Model
Simulated datasets were used to research the effects of the systematic variation of three major variables on the performance of computerized adaptive testing (CAT) procedures for the partial credit model. The three variables studied were the stopping rule for terminating the CATs, item pool size, and the distribution of the difficulty of the items in the pool. Results indicated that the standard error stopping rule performed better across the var…
Item and Scale Information Functions for the Successive Intervals Rasch Model
Simulated data were used to investigate systematically the impact of various characteristics of the threshold values (number, symmetry, and distance between adjacent threshold values) and of the delta values on the distribution of item information in the successive intervals Rasch model. The results revealed that the shift in the peak of the information function away from the scale value of an item depended on the degree of asymmetry of the thres…
An Investigation of Procedures for Computerized Adaptive Testing Using the Successive Intervals Rasch Model
The major objective of the present study was to evaluate basic procedures for performing computerized adaptive testing (CAT) based on the successive intervals (SI) Rasch model. The SI model is designed for measuring attitudes based on Thurstone's successive intervals concept. The SI model was applied to both simulated and real attitude data sets for which the item response data were polytomous. Using simulated data, such variables as item pool si…
The Effect of Population Distribution and Method of Theta Estimation on Computerized Adaptive Testing (CAT) Using the Rating Scale Model
A simulation study was conducted to investigate the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori estimation (EAP) in computerized adaptive testing (CAT) based on Andrich's rating scale model. Comparisons were made among MLE and EAP with a normal prior distribution and EAP with a uniform prior distribution within two data sets: one generated using a normal trait distribution and the other using…
A Comparison of Maximum Likelihood Estimation and Expected a Posteriori Estimation in CAT Using the Partial Credit Model
A simulation study was conducted to investigate the application of expected a posteriori (EAP) trait estimation in computerized adaptive tests (CAT) based on the partial credit model and compare it with maximum likelihood trait estimation (MLE). The performance of EAP was evaluated under different conditions: the number of quadrature points (10, 20,40, and 80) and the type of prior distribution (normal and uniform). The relative performance of ML…
Exploring Asian American racial identity
In this study the authors used cluster analysis to create racial identity profiles for a sample of Asian Americans using the People of Color Racial Identity Attitudes Scale (PCRIAS). A four-cluster solution was chosen: each cluster corresponded to one PCRIAS subscale and was named accordingly. Scores on the Asian American Racism-Related Stress Inventory and the Color-Blind Racial Attitudes Scale were compared across clusters. As expected, the Dis…
A New Stopping Rule for Computerized Adaptive Testing
The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared with that of the minimum standard error stopping rule and a modified version of the minimum in…
Balancing Flexible Constraints and Measurement Precision in Computerized Adaptive Testing
Managing test specifications—both multiple nonstatistical constraints and flexibly defined constraints—has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT, and the weighted penalty model in balancing multiple flexible constraints and maximizing measurement prec…
Panel Design Variations in the Multistage Test Using the Mixed-Format Tests
This study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized adaptive test (CAT) conditions provided baseline comparisons. Three passing rate conditions were also …
Comparison of Exposure Controls, Item Pool Characteristics, and Population Distributions for CAT Using the Partial Credit Model
This study investigated item exposure control procedures under various combinations of item pool characteristics and ability distributions in computerized adaptive testing based on the partial credit model. Three variables were manipulated: item pool characteristics (120 items for each of easy, medium, and hard item pools), two ability distributions (normally distributed and negatively skewed data), and three exposure control procedures (randomes…
The Impact of Varied Discrimination Parameters on Mixed-Format Item Response Theory Model Selection
Whittaker, Chang, and Dodd compared the performance of model selection criteria when selecting among mixed-format IRT models and found that the criteria did not perform adequately when selecting the more parameterized models. It was suggested by M. S. Johnson that the problems when selecting the more parameterized models may be because of the low variance of the discrimination parameters used to generate the data. This simulation study reproduced…
A Comparison of Exposure Control Procedures in CATs Using the 3PL Model
This study compares the progressive-restricted standard error (PR-SE) exposure control procedure to three commonly used procedures in computerized adaptive testing, the randomesque, Sympson–Hetter (SH), and no exposure control methods. The performance of these four procedures is evaluated using the three-parameter logistic model under the manipulated conditions of item pool size (small vs. large) and stopping rules (fixed-length vs. variable-leng…
The Development of MST Test Information for the Prediction of Test Performances
The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the validity of the proposed method in both measurement precision and classification accuracy. The resul…
Mathematics (13 works) · Psychometric Methodologies and Testing (13 works) · Statistics (13 works) · Computer Science (10 works) · Advanced Statistical Modeling Techniques (9 works) · Psychometrics (9 works) · Computerized adaptive testing (7 works) · Econometrics (7 works) · Item response theory (5 works) · Psychology (5 works)