Contrast Variable Potentially Providing a Consistent Interpretation to Effect Sizes

Various effect sizes have been proposed. However, different effect size measures are suitable for different types of data, and the interpretations of effect sizes are generally arbitrary and remain problematic.

In this article, the concepts of contrast variable, its standardized mean (SMCV) and c + -probability are explored to link together the commonly used effect sizes including the probabilistic index and ratios of mean difference to variability. A contrast variable can provide both a probabilistic meaning and an index of signal-to-noise ratio to interpret the strength of a comparison, which offers us a strong base to classify the strength of a comparison. Contrast variable, SMCV and c + -probability not only give interpretations to both Cohen’s and McLean’s criteria but also work effectively and consistently for either relationship or group comparison in either independent or correlated situations and in either two or more than 2 groups.

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Bayesian Analysis Using Power Priors with Application to Pediatric Quality of Care

Investigators conducting new research often have access to data from previous studies, and in such cases it is not only scientifically reasonable but also statistically advantageous to incorporate this information into the current analysis.

Consider, for example, the common scenario in which a funding agency finances research incrementally, first requiring a small pilot or feasibility study before funding a more elaborate trial. In such cases, it can be beneficial to incorporate the pilot data into the subsequent analysis to increase the power to detect treatment effects. One strategy for synthesizing results across studies is through a Bayesian modeling approach. Because Bayesian methods can incorporate historical information through a prior distribution, they provide a natural framework for updating information across studies.

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Biplot Simulation to Determine the Growth Rate of Body Dimension in Local Bali Ducks

Biplot simulation using factor analysis rotation promax kapa 90 was conducted to determine the growth rate of body dimension in female Bali duck of 0-16 week-old. The result of the biplot simulation showed that the body dimension of female Bali ducks that belongs to slow growth rate was in quadran II including the length of radius ulna, femur, tarsal and humerus. 

The body dimensions of female Bali ducks with the moderate growth rates were in quadrant I such as the length of carpal, chest circumference, body weight, the length necks, the length of digital 1 and the length of head. The body dimension with fast growth rate such as head circumference, neck circumference, abdominal circumference, and the length of digital 2, 3 and 4, and the length of tibia-fibula. Based on the ages, the coordinates distances in two dimension Eigen vector space were as follows. At the most distance position was at the age of 0-2 weeks, followed by the age of 2-4 weeks, and finally with closest distance was at the age of maturity.