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Analysis of Categorical Data Under a Full Model

In: Complex Surveys

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  • Parimal Mukhopadhyay

    (Indian Statistical Institute)

Abstract

Nowadays, large-scale sample surveys are often conducted to collect data to test different hypotheses in natural and social sciences. Such surveys often use stratified multistage cluster design. Data obtained through such complex survey designs are not generally independently distributed and as a result multinomial models do not hold in such cases. Thus, the classical Pearson statistic and the related usually used test statistic would not be valid tools for testing different hypotheses in these circumstances. Here we propose to investigate the effect of stratification and clustering on the asymptotic distribution of Pearson statistic, log-likelihood ratio statistic for testing goodness-of-fit (simple hypothesis), independence in two-way contingency tables, and homogeneity of several populations.

Suggested Citation

  • Parimal Mukhopadhyay, 2016. "Analysis of Categorical Data Under a Full Model," Springer Books, in: Complex Surveys, chapter 0, pages 97-133, Springer.
    • Handle: RePEc:spr:sprchp:978-981-10-0871-9_4
    DOI: 10.1007/978-981-10-0871-9_4
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