The main purpose of this paper is to introduce and study the behavior of minimum ϕ -divergence estimators as an alternative to the maximum-likelihood estimator in latent class models for binary items. As it will become clear below, minimum ϕ -divergence estimators are a natural extension of the maximum-likelihood estimator. The asymptotic properties of minimum ϕ -divergence estimators for laten...

In clinical study, calculation for sample size is often done using the frequentist framework. However, several methods of calculation using the Bayesian framework have been proposed. In this paper, we propose a method for the determination of sample sizes using the index θ = P ( π1 > π2|X1, X2 ) , where X1 and X2 denote the binomial random variables for trials n1 and n2 and parameters π1 and π2...

In this article we have proposed an integrated system for measurement of important features from 3D tissue images. We propose a segmentation technique, where we combine several methods to achieve a good degree of automation. Important histological and cytological three-dimensional features and strategies to measure them are described.

In this paper, we introduce a principled algorithmic approach for Fourier ptychographic imaging of dynamic, time-varying targets. To the best of our knowledge, this setting has not been explicitly addressed in the ptychography literature. We argue that such a setting is very natural, and that our methods provide an important first step towards helping reduce the sample complexity (and hence acq...

(a) larger sample size so that the result is more precise, appropriate subgroup analysis is more feasible, and there is a lower risk of an apparently "negative" result when the treatment is, in truth, effective; (b) quicker results before people lose scientific and commercial interest in the treatment and before it is modified or the theoretical indications for it are changed; (c) wider dissemi...

Very often statisticians have to deal with the problem of sample size calculation. However this is one of the most difficult questions to be answered since it depends on many considerations, assumptions and restrictions on the real problem being solved. In this paper we develop some methods, based on credible intervals, to calculate sample sizes for proportions and correlations.

We simulated multistate capture histories (CHs) by varying state survival (ϕ), detection (p) and transition (ψ), number of total capture occasions and releases per capture occasion and then modified these scenarios to mimic false rejection error (FRE), a common misidentification error, resulting from the failure to match samples of the same individual. We then fit a multistate model and estimat...

We developed a new analytic proof and conducted Monte Carlo simulations to assess the effects of methodological and statistical artifacts on the relative accuracy of intercept- and slope-based test bias assessment. The main simulation design included 3,185,000 unique combinations of a wide range of values for true intercept- and slope-based test bias, total sample size, proportion of minority g...

The problem of sample size determination based on three commonly used non-parametric rank based tests, namely, one-sample Wilcoxon's rank sum test, two-sample's Wilcoxon's rank sum test, and the rank-based test for independence is studied. Explicit formulas for variabilities of the test statistics under the alternative hypotheses are derived. Consequently, close forms of power functions of thes...

While manual tracing is the method of choice in measuring hippocampal volume, its time intensive nature and proneness to human error make automated methods attractive, especially when applied to large samples. Few studies have systematically compared the performance of the two techniques. In this study, we measured hippocampal volumes in a large (N = 403) population-based sample of individuals ...