Notes on estimation of the intraclass correlation under the AB/BA crossover trial

Under the AB/BA crossover trial, we focus our attention on estimation of the intraclass correlation in normal data. We develop both point and interval estimators in closed form for the intraclass correlation. We employ Monte Carlo simulation to study the performance of these estimators in a variety of situations. We note that the estimators developed here for the intraclass correlation remain valid even when there are possibly unexpected carry-over effects.     

Improved Estimates and Confidence Intervals for Regenerative Simulation

In regenerative simulation, one frequently requires an estimate or a confidence interval for the ratio of the means of the two components of a certain bivariate random quantity. Estimation of this ratio has been studied by many authors and most recently by Asmussen and Rydén(2010 Asmussen, S., Rydén, T. (2010). A note on skewness in regenerative simulation. Communications in Statistics—Simulation and Computation 40: 45–57.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). Here, we propose an estimate that performs better than the best of the known estimates. Our estimate is also lot simpler than the best known estimate.     

Estimating the Size of Street-Dwelling Populations Using Mark-Resighting Counts

Mark-resighting constitutes an advanced technology for estimating animal abundance. Joint hypergeometric maximum likelihood, Minta-Mangel and Bowden estimators are usually adopted with mark-resighting data. In presence of any tendency of animals to aggregate into groups, the Bowden estimator is the sole reliable method, providing that marks are quite evenly distributed among groups. In some cetacean surveys, marking disturbances are avoided through natural marking. Natural marking with Bowden criterion is used to estimate the abundance of street-dwelling populations. The marked individuals are persons identified and recorded in the initial part of the survey and recognizable in subsequent occasions. A simulation helps determine the performance of the Bowden estimator under a wide set of situations, taking into account key features of street-dwelling populations. When marked individuals are evenly distributed among groups, the strategy is efficient.     

Status quo bias in decision making

Most real decisions, unlike those of economics texts, have a status quo alternative—that is, doing nothing or maintaining one's current or previous decision. A series of decision-making experiments shows that individuals disproportionately stick with the status quo. Data on the selections of health plans and retirement programs by faculty members reveal that the status quo bias is substantial in important real decisions. Economics, psychology, and decision theory provide possible explanations for this bias. Applications are discussed ranging from marketing techniques, to industrial organization, to the advance of science.     

A Characterization of the Normal Family of Distributions Based on the Bias of the Maximum Likelihood Estimator

This paper characterizes the family of Normal distributions within the class of exponential families of distributions, via the structure of the bias of the maximum likelihood estimator Θ _n of the canonical parameter Θ . More specifically, when E _θ ( Θ n ) – Θ = (1/ n ) Q ( Θ ) + o (1/ n ), the equality Q ( Θ ) = 0 proves to be a property of the Normal distribution only. The same conclusion is obtained for the one-dimensional case bt assuming that Q ( Θ ) is a polynomial of Θ .     

Order statistics from non-identical right-truncated Lomax random variables with applications

In this paper, we derive some recurrence relations for the single and the product moments of order statistics from n independent and non-identically distributed Lomax and right-truncated Lomax random variables. These recurrence relations are simple in nature and could be used systematically in order to compute all the single and product moments of all order statistics in a simple recursive manner. The results for order statistics from the multiple-outlier model (with a slippage of p observations) are deduced as special cases. We then apply these results by examining the robustness of censored BLUE's to the presence of multiple outliers. Received: November 30, 1998; revised version: March 8, 2000     

The cycle of cyberbullying: Some experience required

Findings from a survey of 1,602 middle school and high school students suggests despite heavy use of social media, adolescents believe they are less likely than peers to be victims of cyberbullying and less likely to bully others. The results suggest a cycle of perceptions and behaviors: victims of cyberbullying bully others. Adolescents who believe they are likely to be bullied acknowledge they are likely to continue bullying others and are also likely to blame victims for “bringing it on themselves.”     

The general class of chain estimators for the ratio of two means using double sampling

A wider class of chain based estimators for the ratio of two means of a finite population has been proposed by using two auxiliary variables. Singh et al.(1994) is a particular case of this class.     

Transformation and Smoothing in Sample Survey Data

Abstract. We consider model‐based prediction of a finite population total when a monotone transformation of the survey variable makes it appropriate to assume additive, homoscedastic errors. As the transformation to achieve this does not necessarily simultaneously produce an easily parameterized mean function, we assume only that the mean is a smooth function of the auxiliary variable and estimate it non‐parametrically. The back transformation of predictions obtained on the transformed scale introduces bias which we remove using smearing. We obtain an asymptotic expansion for the prediction error which shows that prediction bias is asymptotically negligible and the prediction mean‐squared error (MSE) using a non‐parametric model remains in the same order as when a parametric model is adopted. The expansion also shows the effect of smearing on the prediction MSE and can be used to compute the asymptotic prediction MSE. We propose a model‐based bootstrap estimate of the prediction MSE. The predictor produces competitive results in terms of bias and prediction MSE in a simulation study, and performs well on a population constructed from an Australian farm survey.     

Equality of two blues and ridge-type estimates

Equality is shown of the g-inverse and Moore-Penrose inverse representation of the BLUE in the general linear model. The proof is based on a matrix identity which allows also to establish a functional relationship between the BLUE and Ridge-type estimates.