Spss statistical software version 19.0 for windows

Statistical analysis was performed using SPSS statistical software version 19.0 for Windows (SPSS Inc., Chicago, IL). After testing for normal distribution by mean of the Kolmogorov–Smirnov test, we applied nonparametric tests. Matched data were compared with Wilcoxon signed rank test, while differences between groups were assessed using the Mann–Whitney U‐test. Values were expressed as medians and ranges, while categorical variables were described as absolute numbers and percentages.
Correlation analysis was then used to identify potential influencing factors for IQ amelioration in the whole sample. Nonparametric correlation coefficient (Spearman's Rho) was used, considering the presence of non‐normally distributed variables.
Clinical variables analyzed in relation to cognition were the presence and type of mutation (missense, nonsense, splice site, deletion, or frame shift), CSF/blood glucose ratio, and patient's age at the time of KD implementation.

Statistical analysis used SPSS statistical software, version 19.0 for WINDOWS (SPSS Inc., Chicago, IL, USA). All data in text, figures, and tables are expressed as mean ± SD. The normal distribution of variables (Gaussian data) was assessed using the Kolmogorov–Smirnov test. For continuous data, comparison among variables were performed using Student’s tests for Gaussian data and using Mann–Whitney rank sum tests for non-normally distributed data. Categorical data were analyzed using the χ² test or Fisher’s exact probability test, as appropriate. Correlations were assessed by Spearman´s rank correlation. A p-value <0.05 was considered statistically significant.

Data were collected and expressed as number, percentage, and mean ± standard deviation. The statistical result of pain scores was expressed as median with interquartile range. Normally distributed data were compared between groups using the unpaired Student's t-test, and continuous variables with a non-Gaussian distribution were presented as median with ranges and compared between groups using Mann-Whitney U test. Group differences with nominal variables were analyzed using Chi-square or Fisher's exact tests for proportions. A p value < 0.05 was considered to be statistically significant. All statistical data were analyzed using the SPSS statistical software version 19.0 for Windows (SPSS Inc., Chicago, IL, USA).

Statistical analysis used SPSS statistical software, version 19.0 for WINDOWS (SPSS Inc., Chicago, IL, USA). Data are expressed as mean ± SEM. The normal distribution of variables to characterize differences in the analyzed parameters was assessed using the Kolmogorov-Smirnow test. Comparisons among variables were made by paired Student's tests or alternatively by a non-parametric test (Mann-Whitney rank sum tests). In the case of multiple comparison, a Kruskal-Wallis test followed by a Dunn's multiple comparisons test was performed. Categorical data were analyzed using the c² test or Fisher's Exact Probability Test, as appropriate. A study of the relationship among parameters was also carried out using Spearman's rank correlation. Bonferroni correction was further applied in correlation and multiple comparison analyses. Differences were considered significant at P < 0.05.

The person-years for cancer risk were recorded from the index date to the date of cancer diagnosis, death, or the end of 2007, whichever was earlier. The incidence densities (per 100,000 person-years) of cancer occurrence in the CHD cohort were then calculated. The association between CHD and cancers by SIRs was examined. The SIRs were calculated as the number of observed cancer cases among the CHD cohort divided by the number of expected cancer cases according to the national age-, gender-, and period-specific cancer rates from the yearly reports of cancer rates from the Taiwan Cancer Registry. The registry provided a database of cancer-related data for various research efforts and was made available upon request (S1 Table). The 95% confidence interval (CI) of SIR was calculated using Byar’s approximation [46 ].
The Cox proportional hazard model with hazard ratio (HR) was used to analyze the risk factors for the occurrence of cancer. Control variables such as age, gender, co-morbidities, and medical radiation examination were included in the model.
Microsoft Office Excel 2003 (Microsoft Corporation, Redmond, Washington, USA) and the SPSS statistical software version 19.0 for windows (SPSS Inc., Chicago, IL, USA) were used to perform the statistical analysis. Statistical significance was set at p<0.05.