Spss ver 18.0 for windows

SPSS ver. 18.0 for Windows (SPSS Inc., Chicago, IL, USA) was used for statistical analysis. We assessed the difference in BADS scores between ambulatory vs. non-ambulatory groups and patients with abnormal findings on MRI vs. patients without abnormal findings on MRI, using independent t-test. The p-values below 0.05 were defined as statistically significant. Analysis of covariance (ANCOVA) was used for statistical analysis of VBM. We performed a comparative analysis of grey matter increase and decrease between the patient group and control group. To adjust for type 1 error in statistical processing, familywise error rate (Bonferroni correction) was used at the statistical significance of p=0.05. The minimum pixel count was set as 300 pixels [21 (link)]. To compare DTT and MEP findings between dyskinetic CP patients and healthy controls, independent samples t-test was used, and p<0.05 was defined as statistically significant.

The changes in the evaluation parameters from the initial to the 2nd week or 4th week evaluation were analyzed using the Kruskal-Wallis test to determine the statistical difference among three groups. For post-hoc, the Bonferroni method was used. Mann-Whitney U tests were performed in each category between the groups. The significance level of the post-hoc was 0.05/3=0.017. Perprotocol (PP) analysis was performed using the data of the subjects who completed the entire four-week study period, and the intention-to-treat (ITT) analysis was also performed using the data of all the subjects who completed or withdrew from the study, along with the last observation carried forward method. All statistical analyses were performed using the SPSS ver. 18.0 for Windows (SPSS Inc., Chicago, IL, USA). Statistical significance was considered when p-value was less than 0.05.

SPSS ver. 18.0 for Windows (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. The positive and negative MEP responses on the MRC scale and the distribution of the MEP amplitude ratios were analyzed using cross-tabulation. The independent t-test was used to determine significant differences in the functional test scores measured at the times of hospitalization and discharge between patients with positive and negative MEP responses. Receiver operating characteristics curves were used to determine the cutoff values, and the area under the curve (AUC) was used to obtain the minimum MEP amplitude ratio for patients who performed the HFTs and were capable of ambulation and stair climbing. Spearman correlation test was used to assess the associations between the MEP amplitude ratio, MRC scale, the HFTs, and the K-MBI. The p-values less than 0.05 were considered significant.

All data was expressed as mean ± SD (SD: standard deviation) or the number of the
subjects with percentage, where appropriate. Statistical analysis was done using
the SPSS ver. 18.0 for windows (SPSS Inc., Chicago, IL). Differences in
demographic and socio-economic characteristics of the subjects between
under-employment, adequate employment and over-employment were analyzed using
the χ² -test. Moreover, differences in work characteristics of the
subjects between under-employment, adequate employment and over-employment were
also analyzed using the χ² -test or analysis of
variance (ANOVA). Furthermore, a multivariate logistic regression analysis was
also performed to identify factors determining satisfaction with work
environment, for which the odds ratio (OR) and 95% confidence interval (CIs)
were calculated. A P-value of <.05 was considered
statistically significant, if applicable, for which P-values
were adjusted for multiple comparisons using Bonferroni’s correction method.