Simultaneous inference for proportions in multivariate stratified random sampling without replacement for service quality control using multiple choice questions
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引用次数: 0
Abstract
Determining the asymptotic distribution of the estimator for parameters of interest when employing complex sampling designs is a methodological issue of extreme importance. This paper addresses the problem of determining the asymptotic distribution of the vector of sample proportions when the survey questionnaire employs multiple-choice questions, as often done in service quality evaluations. Specifically, we consider a stratified sampling design where units within each stratum are selected without replacement, and the multivariate random variable from which the sample is drawn follows a multivariate Bernoulli distribution. The main goal is to obtain a valid asymptotic result under the specific conditions imposed by this design, so as to make statistical inference about the vector of specific parameters of interest, such as the proportion of responses assigned to each subdimension considered in the survey questionnaire.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.