Determinants of Volunteering Within a Social Housing Community

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - In general, research demonstrates that deprivation, education, health, and well-being are determinants of volunteering,...     

Bootstrapping and permuting paired t-test type statistics

We study various bootstrap and permutation methods for matched pairs, whose distributions can have different shapes even under the null hypothesis of no treatment effect. Although the data may not be exchangeable under the null, we investigate different permutation approaches as valid procedures for finite sample sizes. It will be shown that permutation or bootstrap schemes, which neglect the dependency structure in the data, are asymptotically valid. Simulation studies show that these new tests improve the power of the t-test under non-normality.     

Consistency of the Subsample Bootstrap empirical process

In the classical Bootstrap approach the number of distinct observation in the resample is random. To overcome this hitch Rao et al. [Bootstrap by sequential resampling, J. Statist. Plan. Inference 64 (1997), pp. 257–281] have proposed a modified resampling procedure – the so-called Sequential Bootstrap or 0.632-Bootstrap – in which each resample has exactly the same number m ～eq ?0.632 n? of distinct observations. Motivated by this idea we introduce an akin procedure, the Subsample Bootstrap, where additionally even the size of each resample is equal. It will turn out that the Subsample Bootstrap empirical process is consistent for a wide class of Donsker classes.     

Wählen als Gruppenerfahrung?

Lazarsfeld et al. have formulated a voting model, which is based on the influences of group embedding. This essentially means that people adapt their voting behaviour according to their social embeddings. However, the individualisation thesis has recently claimed that group embeddings have become looser and more often contradictory. Can the empiric findings of Lazarsfeld therefore still be valid? This analysis, which is based on a panel study on the Styrian Local Elections 2000, sets out to test the applicability of this voting model. It can be shown clearly, that people are still more likely to vote for the parties, which are popular within their social surroundings. However, when put under cross pressures, people tend to change their party preferences, whereas relevant cross pressures are not only resulting from social embeddings, but also from the evaluation of politicians, issues and so on.     

Combining the t test and Wilcoxon's rank-sum test

In the two-sample location-shift problem, Student's t test or Wilcoxon's rank-sum test are commonly applied. The latter test can be more powerful for non-normal data. Here, we propose to combine the two tests within a maximum test. We show that the constructed maximum test controls the type I error rate and has good power characteristics for a variety of distributions; its power is close to that of the more powerful of the two tests. Thus, irrespective of the distribution, the maximum test stabilizes the power. To carry out the maximum test is a more powerful strategy than selecting one of the single tests. The proposed test is applied to data of a clinical trial.