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Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent associations between the pairs of variables and higher order interactions among more than two variables.
The estimated expected frequencies under the particular models can be found from the iterative proportional fitting. Such type of models is, essentially, the equivalent for the frequency data, of the models for the continuous data used in the analysis of variance, except that interest usually now centres on parameters representing interactions rather than those for the main effects.
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
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
It is the diagram used to display the values graphically in a frequency distribution. The frequencies are graphed as an ordinate against the class mid-points as abscissae. The p
The model which is applicable to the longitudinal data in which the dropout process might give rise to the informative lost values. Specifically if the study protocol specifies the
Lagging indicators: The part of a collection of the economic time series designed to give information about the broad swings in measures of the aggregate economic activity known a
Yate s' continuity correction : When the testing for independence in contingency table, a continuous probability distribution, known as chi-squared distribution, is used as the app
Independent component analysis (ICA) is the technique for analyzing the complex measured quantities thought to be mixtures of other more fundamental quantities, into their fundamen
Odds ratio is the ratio of the odds for the binary variable in two groups of the subjects, such as, males and females. If the two possible states of variable are labeled as 'succe
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if |t | > t = 1.96
Multiple imputation : The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simula
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