Standard descriptive statistics tools were used to describe the material. The differences between measurements in the FASD and control groups (diff = FASD – Control) were analysed as a main endpoint. The main effect was tested using the general linear model (GLM) for repeated measures regarding age, gender and the type of FASD (FAS, pFAS, ARND) as the between subject variables. The age variable was categorized: age for two categories: 0: < = 12 and 1: > 12. The FASD type variable was encoded as 0: ARND, 1: FAS, 2: pFAS. The statistical significance of the differences for individual measurements was tested using the student's T test. All statistical analyses were performed using IBM SPSS Statistics 23 package.
Spss statistics 23 package
Manufactured by IBM
Sourced in United States
SPSS Statistics 23 is a software package for statistical analysis. It provides tools for data management, analysis, and presentation. The software offers a range of statistical techniques, including descriptive statistics, bivariate analysis, and multivariate analysis. SPSS Statistics 23 is designed to assist users in organizing, analyzing, and interpreting data.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using spss statistics 23 package
1
Neurodevelopmental Effects of FASD
2
Comparative Analysis of Novel Biomarkers
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Data are represented as medians with interquartile ranges. Paired data were compared using the Wilcoxon signed-rank test, otherwise the Mann-Whitney U test was used. When comparing more than two groups, the Kruskal Wallis H test was used. P-values <0.05 were considered significant. Graphs were made using GraphPad Prism v6 (San Diego, CA, USA). Statistical analysis was performed using the SPSS Statistics 23 package (IBM, Armonk, NY, USA).
3
Comprehensive Statistical Analysis of Treatment Outcomes
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Standard descriptive statistics tools were used; frequency tables were collected for the categorical variables, extreme values, mean values, and standard deviations were collected for the continuous variables with a normal distribution, and extreme values and quartiles were collected for the continuous variables with another distribution. Survival curves were calculated using the Kaplan–Meier method and compared using the logrank test. The competing risk methodology was used to estimate the cumulative probability of birth after the treatment and disease recurrence. The results are illustrated in the cumulative incidence curves. All estimates are given with a 95% confidence interval. All tests were performed at the statistical significance level of 0.05. The statistical analysis was carried out using the IBM SPSS Statistics 23 package.
4
Parametric Analysis of Quantitative Variables
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The analysed variables had a quantitative character. Basic descriptive statistics were calculated for them, with the Kolmogorov-Smirnov test which demonstrated that the distribution of the majority of the variables was not consistent with the normal distribution. Nevertheless, all variables fulfilled an assumption about not exceeding the skewness value of <−2; 2>, so a decision was taken to carry out parametric analyses—Student’s t-test for two independent groups. In the case of demographic variables such as education and marital status, the application of the nonparametric Kruskall-Wallis test was necessary because of considerable differences in the number of respondents in the groups. Moreover, the Kuskall-Wallis test results were checked by the Dunn post hoc explanatory test and Bonferroni correction. The statistical analyses were performed with IBM SPSS Statistics 23 package. The test results at the level of p ≤ 0.05 were considered statistically significant.
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