Narendra Mulani
Biographic Data
| ID | 784977 |
|---|---|
| NAME | Narendra Mulani |
| GIVEN NAMES | Narendra |
| FAMILY NAME | Mulani |
| SIGNATURE | MULANI N |
| AFFILIATIONS | Rutgers Sexual and Reproductive Health and Rights |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1983 |
| LATEST PUBLICATION YEAR | 1989 |
| H-INDEX | 1 |
On the Use of Component Scores in the Presence of Group Structure
Examination of the properties of component scores in the presence of group structure shows that the first few components extracted, typically viewed as most informative regarding total variance, do not necessarily contain the most information across group differences. A method for identifying informative components that account for across group differences is presented and illustrated
Offending estimates in covariance structure analysis: Comments on the causes of and solutions to Heywood cases
Offending estimates in covariance structure analysis: Comments on the causes of and solutions to Heywood cases
In this article we discuss, illustrate, and compare the relative efficacy of three recommended approaches for handling negative error variance estimates (i.e., Heywood cases): (a) setting the offending estimate to zero, (b) adopting a model parameterization that ensures positive error variance estimates, and (c) using models with equality constraints that ensure nonnegative (but possibly zero) error variance estimates. The three approaches are ev…
A Probabilistic Latent Class Model for Assessing Inter-Judge Reliability
Increasingly behavioral researchers are soliciting cognitive responses in addition to standard attitudinal measures when attempting to assess the effects of persuasive communications. The coding of the elicited cognitive responses generally involves some sort of categorization, typically undertaken by independent judges, and the quality of the data is, to a large degree, evaluated in terms of some reliability coefficient which reflects the extent…
Scaling Models for Categorical Variables: An Application of Latent Structure Models
Journal Article Scaling Models for Categorical Variables: An Application of Latent Structure Models Get access William R. Dillon, William R. Dillon Search for other works by this author on: Oxford Academic PubMed Google Scholar Thomas J. Madden, Thomas J. Madden Search for other works by this author on: Oxford Academic PubMed Google Scholar Narendra Mulani Narendra Mulani Search for other works by this author on: Oxford Academic PubMed Google Sch…
On the Use of Component Scores in the Presence of Group Structure
Examination of the properties of component scores in the presence of group structure shows that the first few components extracted, typically viewed as most informative regarding total variance, do not necessarily contain the most information across group differences. A method for identifying informative components that account for across group differences is presented and illustrated
Scaling Models for Categorical Variables: An Application of Latent Structure Models
Journal Article Scaling Models for Categorical Variables: An Application of Latent Structure Models Get access William R. Dillon, William R. Dillon Search for other works by this author on: Oxford Academic PubMed Google Scholar Thomas J. Madden, Thomas J. Madden Search for other works by this author on: Oxford Academic PubMed Google Scholar Narendra Mulani Narendra Mulani Search for other works by this author on: Oxford Academic PubMed Google Sch…
A Probabilistic Latent Class Model for Assessing Inter-Judge Reliability
Increasingly behavioral researchers are soliciting cognitive responses in addition to standard attitudinal measures when attempting to assess the effects of persuasive communications. The coding of the elicited cognitive responses generally involves some sort of categorization, typically undertaken by independent judges, and the quality of the data is, to a large degree, evaluated in terms of some reliability coefficient which reflects the extent…
Offending estimates in covariance structure analysis: Comments on the causes of and solutions to Heywood cases
Offending estimates in covariance structure analysis: Comments on the causes of and solutions to Heywood cases
In this article we discuss, illustrate, and compare the relative efficacy of three recommended approaches for handling negative error variance estimates (i.e., Heywood cases): (a) setting the offending estimate to zero, (b) adopting a model parameterization that ensures positive error variance estimates, and (c) using models with equality constraints that ensure nonnegative (but possibly zero) error variance estimates. The three approaches are ev…
On the Use of Component Scores in the Presence of Group Structure
Examination of the properties of component scores in the presence of group structure shows that the first few components extracted, typically viewed as most informative regarding total variance, do not necessarily contain the most information across group differences. A method for identifying informative components that account for across group differences is presented and illustrated
Psychology (5 works) · Mathematics (4 works) · Statistics (4 works) · Computer Science (3 works) · Analysis of covariance (2 works) · Artificial Intelligence (2 works) · Artificial Intelligence (2 works) · Consumer Market Behavior and Pricing (2 works) · Covariance (2 works) · Econometrics (2 works)