Procedures and tables for the construction and selection of chain sampling plans ChSP-4A(c1, c2,)r-Part 4

In this part of the series, the notion of average total inspection (ATI) is introduced to ChSP-4A(c1, c2)r plans, minimizing ATI at a given process average, while protection to the consumer is given in terms of average outgoing quality limit and limiting quality level. The procedure is similar to that of Dodge and Roming.     

Designing ChSP-4(c1, c2) plans

In this paper, the notion of average total inspection (ATI) is introduced to ChSP-4(c1,c2) sampling plans. Procedures have been developed for the construction and selection of ChSP-4(c1, c2 plans, minimizing ATI at a given process average, while protection to the consumer is given in terms of the (i) average outgoing quality limit and (ii) limiting quality level.A wide range of c1 and c2 values are considered for developing tables which cover almost all practical situations. The procedure described is similar to that of Dodge and Romig.     

Deconvolution methods for non-parametric inference in two-level mixed models

Summary.  We develop a general non-parametric approach to the analysis of clustered data via random effects. Assuming only that the link function is known, the regression functions and the distributions of both cluster means and observation errors are treated non-parametrically. Our argument proceeds by viewing the observation error at the cluster mean level as though it were a measurement error in an errors-in-variables problem, and using a deconvolution argument to access the distribution of the cluster mean. A Fourier deconvolution approach could be used if the distribution of the error-in-variables were known. In practice it is unknown, of course, but it can be estimated from repeated measurements, and in this way deconvolution can be achieved in an approximate sense. This argument might be interpreted as implying that large numbers of replicates are necessary for each cluster mean distribution, but that is not so; we avoid this requirement by incorporating statistical smoothing over values of nearby explanatory variables. Empirical rules are developed for the choice of smoothing parameter. Numerical simulations, and an application to real data, demonstrate small sample performance for this package of methodology. We also develop theory establishing statistical consistency.     

Outliers in incomplete multiresponse experiments

Identification of outlier vectors in block designs for incomplete multiresponse experiments has been considered. Design is composed of two sets of experimental units. Different numbers of response variables are observed from these two sets. Cook-statistic has been developed for identification of outliers. The developed statistic has been illustrated with a real-life data set. It has been shown that presence of outliers can distort the overall conclusion from an experiment.     

Design for worksystem safety using employees' perception about safety

In this paper, the predictors of work injuries based on Leamon's Man-Machine model are identified in a sociotechnical framework. Several hypotheses are developed and tested to describe the accident/injury phenomena in mining worksystems. Possible designs for improving work-system's safety are specified using scaled Mahalanobis distance (MD). A case control study design is adopted. Five variables namely, age, negative-affectivity, physical-hazards, job-dissatisfaction, and safety-practice are emerged as significant contributors to work injuries for the mines studied. Two most interesting findings obtained through this study are (i) 36% of cases (injured employees) (MD < 1) are unlucky to meet an accident and (ii) 40% of the controls (non-injured employees) (MD > 1) are lucky to be able to avoid an accident. The most probable reason for the former case is the organizational ineffectiveness while that for the latter may be risky adventures of employees which are due to lack of education, awareness, and appropriate training. Based on the MD values for cases and controls, possible design guidelines are suggested. The study categorically identifies the accident situations where engineering control, education and training, and other organizational safety measures are to be adopted.     

Two-stage chain sampling plans chsp-(0,2) and chsp-(l,2) - part 1

This article outlines the structure of a generalized family of two-stage chain sampling plans, extending the concept of two-stage chain sampling plans of Dodge and Stephens (1966) which is an extension of the original work of Dodge (1955). Expressions are derived for the OC curves for two-stage chain sampling plans with (c₁,c₂) = (0,2) and (1,2). In the original work of Dodge (1955) only acceptance numbers of 0,1 were used and in the extension work of Dodge and Stephens (1966) acceptance numbers of (c₁,c₂) = (0,1), (0,2), (1,2), (0,3), (1,3), (0,4) and (1,4) were used with selected sets of values of k₁ and k₂ (the number of lots considered for cumulation in the first and second stage respectively). In this paper the OC curves are derived more generally for any k₁ and k₂combination for two-stage chain sampling plans with (c₁,c₂) = (0,2) and (1,2) and comparisons are made with respect to sample sizes and discriminating power, with the corresponding single and double sampling plans.     

Hierarchical bayes quality measurement plan

Quality Measurement Plan (QMP) as developed by Hoadley (1981) is a statistical method for analyzing discrete quality audit data which consist of the expected number of defects given the standard quality. The QMP is based on an empirical Bayes (EB) model of the audit sampling process. Despite its wide publicity, Hoadley's method has often been described as heuristic. In this paper we offer an hierarchical Bayes (HB) alternative to Hoadley's EB model, and overcome much of the criticism against this model. Gibbs sampling is used to implement the HB model proposed in this paper. Also, the convergence of the Gibbs sampler is monitored via the algorithm of Gelman and Rubin (1992).     

Normal approximation to the hypergeometric distribution in nonstandard cases and a sub-Gaussian Berry–Esseen theorem

In this paper, we consider simple random sampling without replacement from a dichotomous finite population. We investigate accuracy of the Normal approximation to the Hypergeometric probabilities for a wide range of parameter values, including the nonstandard cases where the sampling fraction tends to one and where the proportion of the objects of interest in the population tends to the boundary values, zero and one. We establish a non-uniform Berry–Esseen theorem for the Hypergeometric distribution which shows that in the nonstandard cases, the rate of Normal approximation to the Hypergeometric distribution can be considerably slower than the rate of Normal approximation to the Binomial distribution. We also report results from a moderately large numerical study and provide some guidelines for using the Normal approximation to the Hypergeometric distribution in finite samples.     

Family,marital, and occupational satisfaction for recovering pathological gamblers

This paper describes the efforts of a private gambling treatment program to conduct a retrospective study of pathological gamblers treated in a publicly supported residential program. The Johns Hopkins Center for Pathological Gambling treated approximately 100 pathological gamblers nationwide from 1979 to 1983 in its residential component. Twenty-six gamblers were assessed regarding their recovery status with specific focus on family, marital status and occupational satisfaction. It was hypothesized that the more satisfied patients would display lower frequencies of gambling and that gambling frequency was dependent upon the level of satisfaction. Thirty-one percent of these gamblers reported abstinence. Regression analyses indicated that the recovery of pathological gamblers as measured by frequency of gambling is significantly influenced by job satisfaction, and moderately influenced by marital status and family life satisfaction. Consequently, these factors should be addressed by mental health professionals in research and treatment of pathological gambling.     

Procedures and tables for the construction and selection of chain sampling plans ChSP-4A(c1,c2)r—Part 2

In this paper an approach for designing chain sampling plans ChSP-4A(c1,c2)r indexed by acceptable quality level and limiting quality level under the conditions of binomial model and a procedure of designing plans for fixed sample sizes minimizing the sum of weighted risks are described.