354,491 research outputs found
Imputation vs. Estimation of Finite Population Distributions
No full textEstimates of the distribution of hourly wage rates for employees are an important output for a national statistics agency. However, many employees are not paid by the hour and so their hourly wage rate data are effectively missing in a survey that attempts to collect this information. A standard approach in this situation is to impute these missing values using derived measures of this wage rate based on salary and hours worked data also collected in the survey. This paper contrasts this imputation approach with direct estimation of the wage rate distribution using the derived wage rate variable as an auxiliary. In particular, we focus on data obtained in the 2002 UK New Earnings Survey and use simulation based on actual and derived hourly wage rate data collected in this survey to compare two imputation approaches, one based on substituting the derived wage rate values for the missing actual values, the other using nearest neighbour imputation based on the derived wage rate, with two estimation approaches that use this variable as an auxiliary. The first of these is a semi-parametric extension of the Chambers and Dunstan (1986) estimator of the finite population distribution function, the other is a calibrated spline-based estimator of this function recently suggested by Harms and Duchesne (2004). Our conclusion is that an approach based on the semi-parametric estimator is best for these data. However, confidence interval estimation remains an open problem
Calibrated Weighting for Small Area Estimation
No full textCalibrated weighting methods for estimation of survey population characteristics are widely used. At the same time, model-based prediction methods for estimation of small area or domain characteristics are becoming increasingly popular. This paper explores weighting methods based on the mixed models that underpin small area estimates to see whether they can deliver equivalent small area estimation performance when compared with standard prediction methods and superior population level estimation performance when compared with standard calibrated weighting methods. A simple MSE estimator for weighted small area estimation is also developed
What If... ? Robust Prediction Intervals for Unbalanced Samples
No full textA confidence interval is a standard way of expressing our uncertainty about the value of a population parameter. In survey sampling most methods of confidence interval estimation rely on “reasonable” assumptions to be true in order to achieve nominal coverage levels. Typically these correspond to replacing complex sample statistics by large sample approximations and invoking central limit behaviour. Unfortunately, coverage of these intervals in practice is often much less than anticipated, particularly in unbalanced samples. This paper explores an alternative approach, based on a generalisation of quantile regression analysis, to defining an interval estimate that captures our uncertainty about an unknown population quantity. These quantile-based intervals seem more robust and stable than confidence intervals, particularly in unbalanced situations. Furthermore, they do not involve estimation of second order quantities like variances, which is often difficult and time-consuming for non-linear estimators. We present empirical results illustrating this alternative approach and discuss implications for its use
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
The New Era
No full textWeekly newspaper from Dilworth, Oklahoma that includes local, state, and national news along with advertising
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