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4.7 Data Analysis 1. Descriptive Statistic
For numeric data descriptive analysis has been done such as mean±SD for normal distribution data, median minimum-
maximum for not normal distribution data, and nominal data presented in frequent data form.
2. Normality Test
For numeric data Kolmogorov Smirnov normality test has been done, if the data was not in normal distribution, the
hypothesis test will be done with assumption the data in normal distribution
with data
transformation through
logistic transformation. The data was normal if p0,05.
3. Comparison Test For paired mean group test, before the comparison test being
done, homogeneity group varians test with Levene test. Comparison test was done with statistical test based on
homogeneity data from Levene test result. Mean test between each group will be done with parametric test if the data in normal
distribution and the variant is numerical. Paired student t test conduct hypothetical test to know mean difference between 2
groups. If after numerical data transformation has been done the result was not normal distribution, then hypothetical test will be
done with non-parametric analysis Mann-Whitney, with presenting median interquartile data. Chi-Square analysis also
done in this bivariate test to look relationship pattern and OR magnitude on each independent variable.
4. Multivariate Test
Multivariate Test can be used to look relationship between one or more dependent variable with one or more independent
variable. This test also used to look contributive relationship from various independent variable to dependent variable or to control
confounding variable, so that relationship between independent variable hypotheses with dependent variable can be seen clearly.
53 Logistic regression analysis has been done to control confounding
variable, so that the impact of independent variable can be seen between dependent variable with nominal scale. Presented
Estimated Odd Ratio OR with Confidence Interval 95. 5. Path Analysis
To look direct relationship between HOMA-IR, IGF-1, IL-6 and hsCRP to prostate hyperplasia and indirect relationship
between HOMA-IR to prostate hyperplasia through IGF-1 elevation.
6. Significancy level α of this research assigned to probability value p less than 0,05. Statistical test with software SPSS for
Mac 21 version and AMOS 23 version.
5. Result 5.1 Basic Characteristics of Research Subjects
A total 80 samples of male included in this study. Forty samples as the case group, with prostate hyperplasia and 40 samples as a
control, with mean age of 62 years old. After the normality test data by Kolmogorov-Smirnov test, and after the logarithm
transformation, a several variables in this study has an abnormal distribution, like hs-CRP, IL-6, fasting insulin, fasting blood
glucose and 2-hour PP, HOMA-IR, TG, SC, body weight, BMI, and waist circumference p 0.05.
Baseline characteristics of Research Subjects Demographic Characteristics and Nutrition Status from the group case Ob-Ab
with Prostate Hyperplasia and control group Ob-Ab without prostate hyperplasia. Basic characteristics data of this study are
presented in Table 5.1.
Table 5.1 Basic demographic characteristics of study population Demographic characteristics dan Nutrition Status
about case Abdominal obesity patient with prostate hyperplasia and control Abdominal obesity patient
without prostate hyperplasia.