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Hot deck is a method broadly used in surveys for imputing the missing values. In its easiest form the method includes sampling with replacement m values from the sample respondents Ar to an item y, where m is number of non-respondents to the item and r is the number of the respondents. The sampled values are taken in use in place of the missing values. The precision of imputation is improved by first forming two or more imputation classes making use of control variables observed in all sample units, and then applying the process separately within each imputation class for each item with the missing values.
Observation-driven model is a term generally applied to models for the longitudinal data or time series which introduce within the unit correlation by specifying the conditional
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
Change point problems : Problems with chronologically ordered data collected over the period during which there is known to have been a change in the underlying data generation cou
Resentful demoralization is the possible phenomenon in the clinical trials and intervention studies in which comparison groups not attaining a perceived desirable treatment become
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
Briefly explain the importance of forecasting for managers?
re-reference all these indexes
Outliers - Reasons for Screening Data Outliers are due to data entry errors, subject is not a member of the population that the sample is trying to represent, or the subject i
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of
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