Spss software for windows version 11

We included 98 male patients between the age of 16 to 52 years (mean 30.9 ± 8.0 years) who attended our clinic with symptoms and diagnosis of urethritis. The patients were interviewed face to face using a 9-item survey questionnaire. The patients were asked to fill in a questionnaire that was administered by a physician. This questionnaire was conducted on a one-on-one basis in a private counseling room. The voluntary nature of the study was stressed and informed consent was obtained from each patient. Basic demographic data was obtained along with information concerning the disease, possible source of infection, location of treatment, and reason for choosing the advised treatment. According to their education level, patients were divided into three groups as follows:
Statistical analyses were performed using SPSS software for Windows (version 11.0, SPSS Inc. Chicago, IL, USA). The differences among the groups in terms of age were evaluated by a one-way ANOVA. A Kruskal-Wallis test was performed to assess the differences between the groups’ education levels and for intergroup comparison. This was followed by pair wise comparison of groups using a Mann-Whitney U test. Differences were considered significant when P < 0.05.

Data were entered using SPSS software for Windows (version 11.5) (SPSS Inc., Chicago, IL, USA). For normally distributed continuous variables, means were compared using unpaired t-tests. For continuous variables not normally distributed, the Mann-Whitney U test was performed. Differences in proportions were compared by the chi-square test or Fisher's exact test if the expected number in any cell was ≤5. A probability of less than 0.05 was considered statistically significant. The strength of association of selected associated/risk factors for acute malnutrition was determined by estimating odds ratios (ORs) and their 95% confidence intervals (CIs). All independent variables, for example, birth order, number of siblings, socioeconomic status, parental characteristics, child feeding, and immunisation history, were analysed initially in univariate models and the attributes that were significantly associated with wasting (dependent variable) and biologically plausible were included in logistic regression models.