This paper develops a new asymptotic theory for two-step GMM estimation and inference in the presence of clustered dependence. The key feature of alternative asymptotics is the number of clusters G is regarded as small or fixed when the sample size increases. Under the small-G asymptotics, this paper shows the centered two-step GMM estimator and the two continuously-updating GMM estimators we c...

In this work we present explicit definitions for the sample complexity associated with the Sample Average Approximation (SAA) Method for instances and classes of multistage stochastic optimization problems. For such, we follow the same notion firstly considered in Kleywegt et al. (2001). We define the complexity for an arbitrary class of problems by considering its worst case behavior, as it is...

Many statistics are based on functions of sample moments. Important examples are the sample variance s2(n), the sample coefficient of variation SV (n), the sample dispersion SD(n) and the non-central t-statistic t(n). The definition of these quantities makes clear that the vector defined by (︀∑︀n i=1Xi, ∑︀n i=1X 2 i )︀ plays an important role. In the paper we obtain conditions under which the v...

H seen what is a “sample”, what are the characteristics of a good sample and how to go about constructing it (probability and nonprobability methods), l e t u s n o w u n d e r s t a n d t h e principles of determining what is an “appropriate size” for the sample and how to calculate it for diverse study designs. We also discuss what can go wrong and what precautions you must exert while calcul...

Consider both the classical and some more general invariant decision problems of estimating a continuous distribution function, with the loss function L ( F , a ) = f ( F ( t ) a(t))2h(F(t))dF(t) and a sample of size n from F. It is proved that any nonrandomized estimator can be approximated in Lebesgue measure by the more general invariant estimators. Some methods for investigating the finite ...

BACKGROUND Central to the design of a randomised controlled trial is the calculation of the number of participants needed. This is typically achieved by specifying a target difference and calculating the corresponding sample size, which provides reassurance that the trial will have the required statistical power (at the planned statistical significance level) to identify whether a difference of...

A sample size calculation for logistic regression involves complicated formulae. This paper suggests use of sample size formulae for comparing means or for comparing proportions in order to calculate the required sample size for a simple logistic regression model. One can then adjust the required sample size for a multiple logistic regression model by a variance inflation factor. This method re...

Exact power and sample size calculation for bioequivalence studies with high order crossover designs using statistical software nQuery are presented. Such calculation can be very easily performed, and thus provides a convenient tool for practical usage.

Electropalatography was used to monitor linguapalatal contact patterns in /s/ and /t/. Talkers often compensated incompletely for a bite block, both immediately after its insertion (sample B1) and after 10 min of practice (sample B2). Significant differences in the number of sensors contacted were noted between normal and bite-block samples for both /s/ and /t/. Differences in length of constri...