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Matching is the method of making a study group and a comparison group comparable with respect to the extraneous factors. Generally used in the retrospective studies when selecting cases and controls to control variation in a response variable due to sources other than those which are taken immediately under investigation. Numerous kinds of matching can be recognized, the most common of which is when each case is individually matched with the control subject on the matching variables, for instance sex, age, occupation, etc. When the variable on which the matching takes place is continuous it is generally transformed into a series of categories (such as age), but the second process is to say that two values of the variable match if their difference lies between the defined limits.
This technique is known as caliper matching. Also significant is group matching in which distributions of the extraneous factors are made similar in the groups to be compared.
How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;
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
A name sometimes given to the type of diagram generally used in meta-analysis, in which point estimates and confidence intervals are displayed for all the studies included in the a
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This graph for Cross Correlation Function for RES1, RES1 shows that there is possibly negative autocorrelation as there are alternating spikes; also the first spike is negative whi
Surveys which use lists related with the vital statistics to sample individuals for the further information. For instance, the 1988 National Mortality Follow back Survey sampled de
Bioassay : It is an abbreviation of biological assay, which in its classical form includes an experiment conducted on biological material to determine relative potency of test and
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The procedure for clustering variables in the multivariate data, which forms the clusters by performing one or other of the below written three operations: * combining two varia
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