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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.
Regression to the mean is the procedure first noted by Sir Francis Galton that 'each peculiarity in man is shared by his kinsmen, but on average to the less degree.' Hence the ten
The procedure which targets to use the health and health-related data which precede diagnosis and/or confirmation to identify possible outbreaks of the disease, mobilize a rapid re
The scatter plots of SRES1, RESI1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plots sho
Non linear model : A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the s
Knox's tests: These tests designed to detect any tendency for the patients with a particular disease to form the disease cluster in time and space. The tests are relied on a two-b
The probability distribution of the various observations is required to obtain the run of two successes in the series of Bernoulli trials with the probability of success equal to a
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par
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