Stata 14.2 se for linux

We used skewness and the kurtosis test to check the normality of the supply/demand ratios distribution. Since the distribution of supply/demand ratios was skewed, we log-transformed the supply/demand ratios for subsequent analyses. The variance ratio test was used to test whether the variance of transplant center log supply/demand ratios was different when comparing DSAs, fixed-distance circles, and fixed-population circles. Additionally, we conducted modified Leven’s test (based on median for skewed data) to test whether the variance of transplant center supply/demand ratios was different when comparing DSAs, fixed-distance circles, and fixed-population circles. All statistical tests were two-sided, and a p-value of ≤0.05 was considered statistically significant. We used a histogram to show the distribution of supply/demand ratio under DSAs, fixed-distance circles, and fixed-population circles. We plotted the average supply/demand ratios for the transplant centers in 50 DSAs under fixed-distance and fixed-population circles in color-scaled maps using R version 3.0.1. Darker colors represented higher supply/demand ratio, while lighter colors represented lower supply/demand ratio. All other statistical analyses were performed using Stata 14.2/SE for Linux (Stata Corp., College Station, TX).

Responses were categorized as “willing to donate organs of any type” if they answered “yes” to being willing to be deceased donors or living donors. For closed-ended items with response options of “yes,” “no,” “not sure,” we dichotomized responses, considering a “not sure” response to indicate “no.” Responses to items using a Likert scale was used were also dichotomized into “yes” (for “probably yes” or “definitely yes”) or “no” (for “not sure,” “probably not,” or “definitely not”). We examined associations between a) respondent characteristics and b) knowledge, attitudes and beliefs, and willingness to donate organs using Fisher’s exact and chi-squared tests for categorical variables and Wilcoxon-Mann-Whitney tests for continuous variables. Responses to open-ended questions were analyzed for themes defined by two independent coders.
All analyses were performed using Stata 14.2/SE for Linux (College Station, Texas).

All statistical analyses were performed using Stata 14.2/SE for Linux (Stata Corp., College Station, TX). HCC and non-HCC candidates were compared using chi-squared tests for categorical variables and Wilcoxon rank-sum tests for continuous variables. Comparisons between HCC and non-HCC candidates were made separately for both eras. All tests were two-sided, and a p-value of ≤0.05 was considered statistically significant. Confidence intervals were reported as per the method of Louis and Zeger (15 (link)).