Quantitative analysis of questionnaires : techniques to explore structures and relationships

Quantitative analysis of questionnaires : techniques to explore structures and relationships /

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Bibliographic Details
Main Author: Humble, Steve (Author)
Corporate Author: ProQuest (Firm)
Format: Electronic eBook
Language:English
Published: Abingdon, Oxon ; New York, NY : Routledge, 2020.
Subjects:
SPSS (Computer file)
Stata.
Statistics > Computer programs.
Social sciences > Research > Statistical methods.
Quantitative research > Statistical methods.
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)

MARC

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245 1 0 |a Quantitative analysis of questionnaires :  |b techniques to explore structures and relationships /  |c Steve Humble. 
264 1 |a Abingdon, Oxon ;  |a New York, NY :  |b Routledge,  |c 2020. 
300 |a 1 online resource (xiv, 215 pages) :  |b illustrations (black and white. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
505 0 0 |a Machine generated contents note:   |g 1.  |t Introduction --   |t Criteria for statistical testing --   |t Types of data --   |t Data sets used as example studies --   |t Missing data --   |g 2.  |t Statistical significance and contingency tables --   |t Statistical significance --   |t Contingency tables --   |t How to report contingency tables --   |g 3.  |t Factor analysis: Exploratory --   |t Exploratory factor analysis --   |t Discovering latent factors --   |t Factor analysis for data reduction --   |t Calculating and using latent factors in future analysis --   |t Missing values --   |t How to report factor analysis --   |g 4.  |t Correlation and linear regression --   |t Scatter diagram --   |t Correlation --   |t Spearman's rank correlation coefficient (Spearman's rho) --   |t Kendall's Tau correlation (x) --   |t Correlations between two variables of different scales --   |t How to report correlations --   |t Calculating correlation with Stata and SPSS --   |t Linear regression --   |t Multicollinearity --   |t Multivariate linear regression --   |t Linear regression sample size conditions --   |t How to report linear regression --   |g 5.  |t Factor analysis: Confirmatory --   |t Constructing First Order CFA Models --   |t More complex CFA models --   |t Uncovering structures in questionnaires --   |t Longitudinal measurement invariance --   |t How to report confirmatory factor analysis --   |g 6.  |t Regression: Logistic --   |t Simple logistic regression --   |t Multivariable analysis --   |t Complex multinomial models --   |t How to report logistic regression --   |g 7.  |t Making choices: Discrete choice theory --   |t Stated and revealed preference --   |t simple consumer choice model --   |t Multinomial logistic regression model with socio-economic factors --   |t Ordered logit choice model --   |t range of discrete choice models --   |t How to calculate ordered and ordinal regression --   |g 8.  |t Item response theory --   |t Item response model --   |t Differential item testing --   |t Graded Response Model (GRM) --   |t Partial Credit Models (PCM) --   |t Information function --   |t Reliability of measures when collapsing Likert scale categories --   |t Appendix --   |t Multiple imputation --   |t Distribution fitting --   |t Factor analysis --   |t Correlation --   |t Linear regression --   |t Sample size --   |t Confirmatory Factor Analysis (CFA) --   |t Logistic regression --   |t Marginal effects --   |t Discrete choice theory --   |t Longitudinal data analysis --   |t Item response theory. 
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