The two-period crossover design with baseline measurements

We consider a two-period crossover study in which each patients measured on the response variable at the start as well as at the end of both periods. We examine models in which the carryover effect at the start of the second period may be different from the carryover effect at the end, and in which the correlations between observations decrease as a function of the time between them.

In trials with a relatively short washout period, we recommend that the second baseline measurement not be incorporated into the analysis and that the data be evaluated by analysis of covariance, with the difference between the post-treatment values as the response variable and the first period's baseline value as the covariate. The absence of carryover effects must be assumed.

When the washout period is moderately long (comparable in length to either treatment period), the preferred analysis for a difference between direct treatment effects will again generally be based on the differences between post-treatment values. An analysis based on changes from baseline would, under certain assumptions about the form of the variance-covariance matrix, be preferred only for quite long washout periods and large correlations between observations. Even then, the efficiency of the test for equality of direct effects is improved if the difference between the baseline values is used as the covariate.     

Approximating probabilities of first passage in a particular gaussian process

Shepp (1971) derives the distribution of waiting times of first passage for a particular Gaussian process. However, Shepp notes that for moderate to large waiting tines the expressions for the probability cannot be evaluated either numerically or by asymptotic estimation. Me present a useful approximation for the distribution and expected waiting time for the conditional and unconditional versions of this first passage problem. The probabilities play a role in bounds by Adler (1984) for the probability distribution of the supremum of a particular two-parameter Gaussian field, a detection problem (Lai, 197 3) and the study of signal shape problems in radars (Zakai Ziv, 1969).     

Multiple clusters on the line

Given N events occurring over time, define an n:t cluster as n consecutive events all contained within an interval of length t. In this paper we derive the expectation, variance and approximate distribution of the number of n:t clusters. The results have applications in epidemiological studies of rare diseases.     

Inference for Income Distributions Using Grouped Data

We develop a general approach to estimation and inference for income distributions using grouped or aggregate data that are typically available in the form of population shares and class mean incomes, with unknown group bounds. We derive generic moment conditions and an optimal weight matrix that can be used for generalized method-of-moments (GMM) estimation of any parametric income distribution. Our derivation of the weight matrix and its inverse allows us to express the seemingly complex GMM objective function in a relatively simple form that facilitates estimation. We show that our proposed approach, which incorporates information on class means as well as population proportions, is more efficient than maximum likelihood estimation of the multinomial distribution, which uses only population proportions. In contrast to the earlier work of Chotikapanich, Griffiths, and Rao, and Chotikapanich, Griffiths, Rao, and Valencia, which did not specify a formal GMM framework, did not provide methodology for obtaining standard errors, and restricted the analysis to the beta-2 distribution, we provide standard errors for estimated parameters and relevant functions of them, such as inequality and poverty measures, and we provide methodology for all distributions. A test statistic for testing the adequacy of a distribution is proposed. Using eight countries/regions for the year 2005, we show how the methodology can be applied to estimate the parameters of the generalized beta distribution of the second kind (GB2), and its special-case distributions, the beta-2, Singh–Maddala, Dagum, generalized gamma, and lognormal distributions. We test the adequacy of each distribution and compare predicted and actual income shares, where the number of groups used for prediction can differ from the number used in estimation. Estimates and standard errors for inequality and poverty measures are provided. Supplementary materials for this article are available online.     

Screening for unusual matched segments in multiple protein sequences

Given a sequence of i.i.d. integer valued random variables, we derive the distribution of the minimum sum of any W consecutive variables. We apply these results to evaluate the unusualness of matches (perfect or almost perfect) in multiply aligned sequences, and matches in all possible alignments of sequences.     

Model Order Estimation of a Multivariable Stochastic Process

ABSTRACT

This article presents a procedure allowing us to estimate the minimal order of a state-space representation, for a multivariable stochastic process, from a sequence of observations. The method proposes a statistical rule for testing the rank of a block Hankel matrix of data, since this rank is related to the order of the process. A new information criterion is then developed and used to decide upon the order of the model. In this article we generalize the Aoki C-test. Using two representative data sets as the basis for a Monte Carlo experiment and real data based on Danish economy, we estimate the order of multivariable stochastic processes.     

ARL-Design of S Charts with k-of-k Runs Rules

The standard S chart signals an out-of-control condition when one point exceeds a control limit. It can be augmented with runs rules to improve its performance in detecting assignable causes. A commonly used rule signals when k consecutive points exceed a control limit. This rule can be used alone or to supplement the standard chart. In this article we derive ARL expressions for charts with the k-of-k runs rule. We show how to design S charts with this runs rule, compare their ARL performance, and make a control chart recommendation when it is important to monitor for both increases and decreases in process dispersion.     

The Run Sum R Chart with Fast Initial Response

A fast initial response (FIR) feature for the run sum R chart is proposed and its ARL performance estimated by a Markov chain representation. It is shown that this chart is more sensitive than several R charts with runs rules proposed by different authors. We conclude that the run sum R chart is simple to use and a very effective tool for monitoring increases and decreases in process dispersion.     

KEEP foster-parent training intervention: model description and effectiveness

In this paper, we describe the development and history of the Keeping Foster Parents Trained and Supported (KEEP) foster-parent training intervention. KEEP intervention represents a modified version of the Multidimensional Treatment Foster Care intervention developed by interventionists at the Oregon Social Learning Center and is designed to provide training and support for children ages 5–11 in regular foster care. We also report on the initial findings from a programme of research focused on determining the effectiveness of the intervention. Thus far, the results indicate that the intervention is effective in reducing child behaviour problems and that the effects of the intervention are mediated through changes in parenting behaviour. There is also evidence that the KEEP foster-parent training intervention increases the chances of a positive change of placement (e.g. child reunited with biological parents) and mitigates the negative risk-enhancing effect of a history of multiple placements. We conclude with a discussion of unanswered questions and directions for future research.