Quantitative analysis of questionnaires : techniques to explore structures and relationships /
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| Main Author: | |
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| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Abingdon, Oxon ; New York, NY :
Routledge,
2020.
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| Subjects: | |
| Online Access: | Connect to this title online (unlimited simultaneous users allowed; 325 uses per year) |
Table of Contents:
- Machine generated contents note: 1. Introduction
- Criteria for statistical testing
- Types of data
- Data sets used as example studies
- Missing data
- 2. Statistical significance and contingency tables
- Statistical significance
- Contingency tables
- How to report contingency tables
- 3. Factor analysis: Exploratory
- Exploratory factor analysis
- Discovering latent factors
- Factor analysis for data reduction
- Calculating and using latent factors in future analysis
- Missing values
- How to report factor analysis
- 4. Correlation and linear regression
- Scatter diagram
- Correlation
- Spearman's rank correlation coefficient (Spearman's rho)
- Kendall's Tau correlation (x)
- Correlations between two variables of different scales
- How to report correlations
- Calculating correlation with Stata and SPSS
- Linear regression
- Multicollinearity
- Multivariate linear regression
- Linear regression sample size conditions
- How to report linear regression
- 5. Factor analysis: Confirmatory
- Constructing First Order CFA Models
- More complex CFA models
- Uncovering structures in questionnaires
- Longitudinal measurement invariance
- How to report confirmatory factor analysis
- 6. Regression: Logistic
- Simple logistic regression
- Multivariable analysis
- Complex multinomial models
- How to report logistic regression
- 7. Making choices: Discrete choice theory
- Stated and revealed preference
- simple consumer choice model
- Multinomial logistic regression model with socio-economic factors
- Ordered logit choice model
- range of discrete choice models
- How to calculate ordered and ordinal regression
- 8. Item response theory
- Item response model
- Differential item testing
- Graded Response Model (GRM)
- Partial Credit Models (PCM)
- Information function
- Reliability of measures when collapsing Likert scale categories
- Appendix
- Multiple imputation
- Distribution fitting
- Factor analysis
- Correlation
- Linear regression
- Sample size
- Confirmatory Factor Analysis (CFA)
- Logistic regression
- Marginal effects
- Discrete choice theory
- Longitudinal data analysis
- Item response theory.