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Institutional surveys are the surveys in which the primary sampling units are the institutions, for instance, hospitals. Within each of the sampled institution, a sample of the patient records is selected.
The basic purpose of the two-stage design (compared to the simple random sample) are to reduce the number of institutions which are required to be subsampled, and to ignore constructing a sampling frame of the patient records for the whole population. Stratified sampling including selecting institutions with the differing probabilities based on some institutional characteristic (like size) is typically used to reduce the variability of the estimators.
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.
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
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
Regression diagnostics is the process designed to investigate the suppositions underlying particular forms of regression examination, for instance, homogeneity of variance, norma
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Models which make use of the smoothing techniques such as locally weighted regression to identify and represent the possible non-linear relationships between the explanatory and th
Length-biased sampling : The bias which arises in the sampling scheme based on the visits of patient, when some individuals are more likely to be chosen than others simply because
The problem that the studies are not uniformly probable to be published in the scientific journals. There is evidence that the statistical significance is a main determining factor
Persson Rootze ´n estimator is an estimator for the parameters in the normal distribution when the sample is truncated so that all the observations under some fixed value C are re
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
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