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The main statistical procedure used was conditional process analysis (Hayes, 2013).
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The main statistical procedures in each classification analysis are described as follows.
It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures.
Statistical procedure involved two main processes, exploratory factor analysis and multinomial logistic regression.
The main statistical method used was the mixed procedure in SAS.
The statistical procedure computed the main effect of these cofounders expressed as an adjusted exponential (Beta) with its 95%% Wald confidence interval (95 % Wald CI) as well as the p value.
The main statistical analyses were conducted with the PROC HAPLOTYPE procedure within SAS/GENETICS™ (SAS 9.1.3).
To handle this problem, a statistical procedure designed to search for a hidden main pattern is developed.
PCA is an established statistical procedure to analyze complex datasets and capture their main features.
The main statistical measures are described next.
This study illustrates a statistical procedure for monitoring aftershock sequences to detect anomalies to increase the probability gain of a significantly large aftershock or even an earthquake larger than the main shock.
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