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Auto correlation: The correlation of the internal observations in the time series, generally expressed as a function of the time lag between the observations. It is also used for the correlations between points different distances apart in the set of spatial data (that is spatial autocorrelation). The autocorrelation at lag k, γ(k), is de?ned mathematically as follows
here Xt ; t 0; 1; 2; ... stand for the values of the series and µ is the mean of series.
Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.
Generalized method of moments (gmm) is the estimation method popular in econometrics which generalizes the method of the moments estimator. Essentially same as what is known as the
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
Informed consent: The consent needed from each potential participant former to random assignment in the clinical trial as speci?ed in the year 1996 version of Helsinki declaration
Link functions: The link function relates the linear predictor ηi to the expected value of the data. In classical linear models the mean and the linear predictor are identical
Hazard regression is the procedure for modeling the hazard function which does not depend on the suppositions made in Cox's proportional hazards model, namely that the log-hazard
Play-the-winner rule is a process sometimes considered in the clinical trials in which the response to treatment is positive (a success) or negative (a failure). One of two treatm
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
Confidence interval : A range of the values, calculated from the sample observations which is believed, with the particular probability, to posses the true parameter value. A 95% c
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
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