Download e-book for kindle: Analyzing Complex Survey Data (Quantitative Applications in by Dr. Eun Sul Lee, Dr. Ronald N. Forthofer

By Dr. Eun Sul Lee, Dr. Ronald N. Forthofer

ISBN-10: 0761930388

ISBN-13: 9780761930389

This booklet examines how you can research complicated surveys, and specializes in the issues of weights and layout results. This re-creation accommodates contemporary perform of reading advanced survey info, introduces the hot analytic technique for express facts research (logistic regression), stories new software program and gives an creation to the model-based research that may be valuable examining well-designed, rather small-scale social surveys.

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Extra resources for Analyzing Complex Survey Data (Quantitative Applications in the Social Sciences)

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For this analysis we need to determine if there are a number of PSUs without observations in a particular education-by-gender category. If there are many PSUs with no observation for some education-by-gender category, this calls into question the estimation of the variance–covariance matrix, which is based on the variation in the PSU totals within the strata. The education (3 levels) by gender (2 levels) tabulation by PSU showed that 42 of the 84 PSUs had at least one gender-by-education cell with no observations.

Although BRR and JRR will produce the same results when applied by different users, the bootstrap results may vary for different users and at different tries by the same user, because the replication procedure is likely to yield different results each time. As Tukey (1986, p. 72) put it, ‘‘For the moment, jackknifing seems the most nearly realistic approach to assessing many of the sources of uncertainty’’ when compared with bootstrapping and other simulation methods. The bootstrap method is not implemented in the available software packages for complex survey analysis at this time, although it is widely used in other areas of statistical computing.

44 The formula-based Taylor series approximation (linearization) is perhaps the most widely used method of variance estimation for complex surveys because it is found in most available software. It may be preferable to the replication-based methods (BRR and JRR) for practical reasons, but, as discussed in Chapter 4, it is not applicable for the median or other percentiles and nonparametric statistics. The replication-based methods are more general and can be applied with these statistics, but they require creating and handling the replicates.

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Analyzing Complex Survey Data (Quantitative Applications in the Social Sciences) by Dr. Eun Sul Lee, Dr. Ronald N. Forthofer

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