Elsevier S & T

Categorical Variables in Developmental Research: Methods of Analysis

von Eye, Alexander; Clogg, Clifford C.

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Table of contents
  • Cover
  • Contentsv
  • Contributorsxi
  • Prefacexiii
  • Acknowledgmentsxvii
  • In Memoriamxix
  • Part 1: Measurement and Repeated Observations of Categorical Data1
  • Chapter 1. Measurement Criteria for Choosing among Models with Graded Responses3
  • 1. Introduction3
  • 2. Measurement Criteria for a Model for Graded Responses4
  • 3. Models for Graded Responses9
  • 4. Examples28
  • 5. Summary and Discussion32
  • References34
  • Chapter 2. Growth Modeling with Binary Responses37
  • 1. Introduction37
  • 2. Conventional Modeling and Estimation with Binary Longitudinal Data39
  • 3. More General Binary Growth Modeling42
  • 4. Analyses46
  • 5. Conclusions52
  • References52
  • Chapter 3. Probit Models for the Analysis of Limited Dependent Panel Data55
  • 1. Introduction55
  • 2. Model Specification56
  • 3. Estimation Method61
  • 4. Analysis of Production Output from German Business Test Data68
  • 5. Conclusion72
  • References73
  • Part 2: Catastrophe Theory75
  • Chapter 4. Catastrophe Analysis of Discontinuous Development77
  • 1. Introduction77
  • 2. Catastrophe Theory79
  • 3. Issues in Conservation80
  • 4. The Cusp Model84
  • 5. Empirical Studies89
  • 6. Discussion101
  • References104
  • Chapter 5. Catastrophe Theory of Stage Transitions in Metrical and Discrete Stochastic Systems107
  • 1. Introduction107
  • 2. Elementary Catastrophe Theory111
  • 3. Catastrophe Theory for Metrical Stochastic Systems115
  • 4. Catastrophe Theory for Discrete Stochastic Systems125
  • 5. General Discussion and Conclusion 128 References128
  • Part 3: Latent Class and Log-Linear Models131
  • Chapter 6. Some Practical Issues Related to the Estimation of Latent Class and Latent Transition Par133
  • 1. Introduction133
  • 2. Methods136
  • 3. Discussion144
  • References146
  • Chapter 7. Contingency Tables and Between- Subject Variability147
  • 1. Introduction147
  • 2. Association Variability148
  • 3. The Simulation Procedure150
  • 4. Tests Based on Multinomial Variability152
  • 5. Tests Based on Between-Subject Variability156
  • 6. Procedures with Two Types of Variability161
  • 7. Discussion163
  • References167
  • Chapter 8. Assessing Reliability of Categorical Measurements Using Latent Class Models169
  • 1. Introduction169
  • 2. The Latent Class Model: A Nonparametric Method of Assessing Reliability171
  • 3. Reliability of Dichotomous Measurements in a Prototypical Case174
  • 4. Assessment of Reliability by Group or by Time178
  • 5. Conclusion181
  • References182
  • Chapter 9. Partitioning Chi-Square: Something Old, Something New, Something Borrowed, but Nothing B183
  • 1. Introduction183
  • 2. Partitioning Independence Models184
  • 3. Analyzing Change and Stability190
  • 4. How to Partition Chi-Square195
  • 5. Discussion199
  • References201
  • Chapter 10. Nonstandard Log-Linear Models for Measuring Change in Categorical Variables203
  • 1. Introduction203
  • 2. Bowker's Test204
  • 3. Log-Linear Models for Axial Symmetry205
  • 4. Axial Symmetry in Terms of a Nonstandard Log-Linear Model206
  • 5. Group Comparisons209
  • 6. Quasi-Symmetry210
  • 7. Discussion213
  • References214
  • Chapter 11. Application of the Multigraph Representation of Hierarchical Log-Linear Models215
  • 1, Introduction215
  • 2. Notation and Review216
  • 3. The Generator Multigraph217
  • 4. Maximum Likelihood Estimation and Fundamental Conditional Independencies219
  • 5. Examples222
  • 6. Summary228
  • References229
  • Part 4: Applications231
  • Chapter 12. Correlation and Categorization under a Matching Hypothesis233
  • 1. Introduction233
  • 2. An Interesting Plot234
  • 3. The Binomial Effect Size Display236
  • 4. An Organizing Principle for Interval-Level Variables237
  • 5. Definition of the Matching Hypothesis237
  • 6. A Data Example238
  • 7. Correlation as a Count of Matches241
  • 8. Correlation as a Count of How Many Fall within a Set Range243
  • 9. Data Simulation244
  • 10. Building Uncertainties from Rounding Error into the Interpretation of a Correlation246
  • 11. Discussion247
  • References248
  • Chapter 13. Residualized Categorical Phenotypes and Behavioral Genetic Modeling249
  • 1. The Problem249
  • 2. Weighted Least-Squares Estimation250
  • 3. Proportional Effects Genotype–Environment Correlation Model253
  • 4. Method256
  • 5. Results258
  • 6. Conclusions271
  • References273
  • Index275
Book details
  • Vendor Elsevier S & T
  • SKU 9780127249650
  • ISBN-13 9780080528717
  • Author von Eye, Alexander; Clogg, Clifford C.
  • Category Psychology
  • Subject Statistics

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Description eBook delivery & access Reviews
This book provides developmental researchers with the basic tools for understanding how to utilize categorical variables in their data analysis. Covering the measurement of individual differences in growth rates, the measurement of stage transitions, latent class and log-linear models, chi-square, and more, the book provides a means for developmental researchers to make use of categorical data.

The book covers:
* Measurement and repeated observations of categorical data
* Catastrophe theory
* Latent class and log-linear models
* Applications