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Post stratification adjustment: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplied by a factor so that total sum of the weights for the respondents in the class equals the population sum for the class. The technique is broadly used in household surveys to control the weighted sample totals to known population totals for particular demographic subgroups. For instance, in the US National Health Interview Survey, post stratification by sex, age, and race is employed.
In an experiment, power is a function of 1. The number of variables being measured and the beta level 2. The effect size, internal validity and the beta level 3. The number of part
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
I want to get the quotation of my on-line assignment its based on 1000 words. lecturer provide the video links and we have to watch the videos and highlights the key points also de
It is an informal method of assessing the effect of the publication bias, generally in the context of the meta-analysis. The effect measures from each of the reported study are plo
Attitude scaling : The process of analysing the positions of the individuals on scales purporting to measure attitudes, for instance a liberal-conservative scale, ora risk-willingn
Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu
Last observation carried forward is a technique for replacing the observations of the patients who drop out of the clinical trial carried out over a time period. It consists of su
Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizin
Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl
This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea o
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