Lisa Calvocoressi
Biographic Data
| ID | 6069560 |
|---|---|
| NAME | Lisa Calvocoressi |
| GIVEN NAMES | Lisa |
| FAMILY NAME | Calvocoressi |
| SIGNATURE | CALVOCORESSI L |
| AFFILIATIONS | Yale University, New Haven, CT, USA |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 6 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
A Note on Comparing the Bifactor and Second-Order Factor Models
This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with multidimensional measuring instrument components, where the bifactor model is found consistently inferior to the sec…
On Effect Size Measures for Nested Measurement Models
A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free from an explicit relationship to sample size. The described indices represent the extent to which respec…
Model Selection and Average Proportion Explained Variance in Exploratory Factor Analysis
A procedure for evaluating the average R-squared index for a given set of observed variables in an exploratory factor analysis model is discussed. The method can be used as an effective aid in the process of model choice with respect to the number of factors underlying the interrelationships among studied measures. The approach is developed within the framework of exploratory structural equation modeling and is readily applicable with popular sta…
Adequacy of Communicating Results From Screening Mammograms to African American and White Women
Objective. We examined whether African American women were as likely as White women to receive the results of a recent mammogram and to self-report results that matched the mammography radiology report (i.e., were adequately communicated). We also sought to determine whether the adequacy of communication was the same for normal and abnormal results. Methods. From a prospective cohort study of mammography screening, we compared self-reported mammo…
Adequacy of Communicating Results From Screening Mammograms to African American and White Women
Objective. We examined whether African American women were as likely as White women to receive the results of a recent mammogram and to self-report results that matched the mammography radiology report (i.e., were adequately communicated). We also sought to determine whether the adequacy of communication was the same for normal and abnormal results. Methods. From a prospective cohort study of mammography screening, we compared self-reported mammo…
Adequacy of Communicating Results From Screening Mammograms to African American and White Women
Objective. We examined whether African American women were as likely as White women to receive the results of a recent mammogram and to self-report results that matched the mammography radiology report (i.e., were adequately communicated). We also sought to determine whether the adequacy of communication was the same for normal and abnormal results. Methods. From a prospective cohort study of mammography screening, we compared self-reported mammo…
Model Selection and Average Proportion Explained Variance in Exploratory Factor Analysis
A procedure for evaluating the average R-squared index for a given set of observed variables in an exploratory factor analysis model is discussed. The method can be used as an effective aid in the process of model choice with respect to the number of factors underlying the interrelationships among studied measures. The approach is developed within the framework of exploratory structural equation modeling and is readily applicable with popular sta…
On Effect Size Measures for Nested Measurement Models
A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free from an explicit relationship to sample size. The described indices represent the extent to which respec…
A Note on Comparing the Bifactor and Second-Order Factor Models
This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with multidimensional measuring instrument components, where the bifactor model is found consistently inferior to the sec…
Artificial Intelligence (3 works) · Artificial Intelligence (3 works) · Computer Science (3 works) · Econometrics (3 works) · Mathematics (3 works) · Statistics (3 works) · Index (typography) (2 works) · Model selection (2 works) · Selection (genetic algorithm) (2 works) · Set (abstract data type) (2 works)