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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 plotted on the x-axis against the corresponding sample sizes on y-axis. Because of nature of sampling variability this plot should, in the nonexistence of publication bias, have the shape of the pyramid with a tapering 'funnel-like' peak. Publication bias will tend to skew pyramid by selectively not including studies with small or no significant effects. Such studies predominate when sample sizes are small but are increasingly less ordinary as the sample sizes increase. Thus their absence removes part of the lower left-hand corner of the pyramid. This effect is illustrated in the Figure which is drawn below.
Classification and regression tree technique (CART): The alternative to the multiple regression and associated techniques or methods for determining subsets of the explanatory va
Calibration : A procedure which enables a series of simply obtainable but inaccurate measurements of some quantity of interest to be used to provide more precise estimates of the r
Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is
ain why the simulated result doesn''t have to be exact as the theoretical calculation
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
How is the rejection region defined and how is that related to the z-score and the p value? When do you reject or fail to reject the null hypothesis? Why do you think statisticians
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
elements , importance, limitation, and theories
Longini Koopman model : In epidemiology the model for primary and secondary infection, based on the classification of the extra-binomial variation in an infection rate which might
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
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