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复杂抽样下的统计推断AI 解读

Summary The design of complex samples induces correlations between element values. In stratification negative correlation reduces the variance; but that gain is less for subclass means, and even less for their differences and for complex statistics. Clustering induces larger and positive correlations between element values. The resulting increase in variance is measured by the ratio deff , and is often severe. This is reduced but persists for subclass means, their…

用于标准误估计的平衡重复复制法AI 解读

Balanced repeated replications (BRR) is a general method for computing standard errors. It is useful when mathematical distribution theory is impractical or lacking, and especially for analytical statistics based on complex samples where clustering destroys the independence of observations. Presented are results of methods used to measure standard errors of regression coefficients for several multivariate techniques. The basic designs of the several samples comprised two…

复杂抽样所得指数的标准误AI 解读

Methods of computing standard errors were developed and applied for several statistics of importance in economic and social surveys. These statistics are based on ratio means r = y/x; x is often the variable sample size of complex samples. Some statistics involve weighted sums σWjrj, others concern the relatives R1 = r1/r0 = (y1/x1)/(y0/x0), the ratio of current (1) to base (0) mean. From these relatives the indexes are constructed, and changes, I2 – I1, in the index. We…

抽样调查中的比率估计偏差AI 解读

Sample survey data are commonly expressed by the ratio mean r = y/x, where both y and x are random variables, each the sum of a survey variable. Most commonly, x is simply the sample size and r the sample mean. Simplicity of computing and presenting this mean gives it considerable advantages, particularly in multi-purpose surveys. Though consistent, it is not an unbiased estimator. Our empirical investigations, set in a theoretical framework, show that the bias in most…

抽样调查中的比率估计偏差AI 解读

Sample survey data are commonly expressed by the ratio mean r = y/x, where both y and x are random variables, each the sum of a survey variable. Most commonly, x is simply the sample size and r the sample mean. Simplicity of computing and presenting this mean gives it considerable advantages, particularly in multi-purpose surveys. Though consistent, it is not an unbiased estimator. Our empirical investigations, set in a theoretical framework, show that the bias in most…

多用途样本的有效配置AI 解读

SUMMARY WHEN LISTING addresses within sample blocks for surveys the field interviewer hastily assigns economic ratings of L, M, and H (for low, medium, and high) to dwellings. The means and the standard deviations differ greatly among these strata with regard to socioeconomic characteristics; hence they may be used for allocating different sampling rates to decrease the variance of sample means and totals. Disproportionate sampling rates bring gains in precision for the…