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1 241 protocols using spss version 15

1

Predicting OHSS using AFC and AMH

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Data was entered into the SPSS version 15. The Shapiro-Wilk test was used to assess the normality of data distribution. Quantitative variables were represented as means and standard deviation, and qualitative variables were represented as frequencies and percentages. Chi-square test and Fischer’s exact test were used to compare these variables at the p <0.05 level of significance.
An ROC curve was used to assess the sensitivity and specificity of both AFC and AMH levels for the prediction of OHSS in both groups. The SPSS version 15.0 (SPSS Inc., Chicago, IL, USA) was used for all statistical analyses.
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2

Genetic Factors in Inflammatory Grade

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Hardy–Weinberg equilibrium and allele/genotype frequencies were calculated using SNPStats software [20 (link)]. The association between SNPs and NIA grade and the most accurate model of inheritance were determined by logistic regression analysis and expressed as odds ratio, 95% confidence interval and p value.
Clinical variables were expressed as medians and 1st-3rd quantiles or number of patients and percentages, except for age (median and range). Associations between variables and NIA were assessed by Mann-Whitney U-test or Chi-squared test. Two-tailed p values below 0.05 were considered significant (SPSS version 15.0; SPSS Inc., Chicago, IL, USA).
Subsequently, significant clinical variables and SNPs were analyzed by multivariate logistic regression using a step-backward method, in which none of the variables was forced to be included into the model. ROC analyses were performed to discriminate the power of factors independently associated with inflammatory grade (SPSS version 15.0; SPSS Inc., Chicago, IL, USA).
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3

Assessing Diminished Ovarian Reserve Markers

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Data was entered and analyzed using SPSS version 15. Shapiro Wilk’s test was used to assess normality of data distribution. The quantitative variables including age, duration of infertility, duration of menstrual irregularities, FSH level on day 2 of cycle, antral follicular count on day 2, anti mullerian hormone (AMH) level, age of menarche in years, body mass index and difference between duration of menstrual irregularity and duration of infertility were presented by medians and range. Mann Whitney u test was used to compare groups. Frequency and percentages were computed for qualitative variables, type of infertility and area of residence. Chi square test and Fischer’s exact test were used to compare these variables at p<0.05 level of significance.
A 2×2 contingency table was used to assess sensitivity, specificity, positive predictive value and negative predictive value of both FSH level criteria and AFC level criteria relative to AMH criteria. AMH criterion was selected as a reference to compare the other two criteria because of growing evidence favoring its utility as the marker of choice for DOR (12 (link)).
The kappa statistic was used to ascertain agreement between the FSH level criteria and AMH level criteria, and the AFC criteria and AMH criteria.
SPSS version 15.0 (SPSS Inc., Chicago, IL, USA) was used for all statistical analysis.
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4

Luting Agent Evaluation Through Statistical Analysis

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Statistical analyses were performed using various statistical software packages (SPSS version 15.0, SPSS, Chicago, IL, USA, and Kyplot 5.0, KyensLab, Tokyo, Japan). Equality of variances and the distributions of the results were analyzed by Levine's test and Kolmogorov-Smirnov test, respectively. If an equality of variances or a normal distribution was not shown in some groups, the Steel-Dwass multiple comparison test (Kyplot 5.0) or Mann-Whitney U test (SPSS version 15.0) was conducted. The Steel-Dwass multiple comparison test was performed to verify differences among the luting agents or between the polymerization modes. In addition, the Mann-Whitney U test was used to determine the influence of the priming agent for the three luting agents before and after thermocycling. A significance level of 5% was set for each analysis.
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5

Evaluating Shrimp Growth and Nutritional Outcomes

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Survival data were normalized using the arcsine transformation prior to statistical analysis. In order to evaluate the differences between all treatment groups, data on growth and survival parameters of all treatments were analyzed using one-way analysis of variance (One-way ANOVA) followed by Duncan Post-Hoc Test with 95% confidence intervals using statistical software SPSS ® Version 24.0.
Student t-test was used to compare nutritional properties between two different feeds (commercial pellet and ex-situ biofloc), whereas one-way analysis of variance (One-way ANOVA) followed by multiple comparison test (Tukey; p < 0.05) was used to compare among shrimp samples-fed with three different treatments by SPSS ® Version 15.0.
Relative fold change of gene expression among shrimp samples-fed with three different treatments was analyzed using one-way analysis of variance (One-way ANOVA) followed by Duncan Post-Hoc Test (p < 0.05) using SPSS ® Version 15.0.
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6

Statistical Analysis of Categorical Data

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Statistical analysis was performed using the SPSS version 15.0 statistical software (IBM Corp., Armonk, NY). Categorical variables were presented as frequency and percentage, and numerical variables as mean±SD. The Chi-square was used to test the association between categorical outcome variables. Differences were considered statistically significant with p<0.05.
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7

Comparative Statistical Analysis Protocol

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All data analyses were performed using SPSS, version 15.0, software (IBM Corp.). Data are presented as means ± standard deviations. For comparisons between two groups, we used unpaired, two-tailed Student’s t tests. For comparisons among multiple groups, we used one-way ANOVA with Bonferroni’s post hoc test. For all experiments, p < 0.05 was considered to be significant. All inclusion/exclusion criteria were preestablished, and no samples or animals were excluded from the analysis. No statistical method was used to predetermine the sample size. The experiments were randomized, and the investigators were blinded to allocation during experiments and outcome assessment. The same sample was not measured repeatedly.
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8

Amflow® Assisted Ventilation Accuracy

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The primary outcome measure of the study was the percentage of appropriate VT which was within 10% range of the target volume: (1) 315–385 ml for 350 ml target, (2) 450–550 ml for 500 ml target, and (3) 630–770 ml for 700 ml target. The secondary outcomes were appropriate RR when the participants deliver the exact number of target ventilations per minute. For comparing categorical variables, the chi-squared test was used. For comparing continuous variables, we used the paired t-test if variables were normally distributed. If continuous variables were not normally distributed, the Wilcoxon signed-rank test was used. Data were analysed using SPSS version 15.0 (IBM Corporation, Chicago, IL, USA); differences with p < 0.05 were considered to be statistically significant. Distribution bar plots were used to illustrate differences in VT and VT between Amflow®-assisted and conventional ventilation.
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9

Comparative Analysis of POAG and Controls

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All statistical tests were performed using IBM SPSS version 15.0 (SPAA Inc., Chicago, IL.)
The qualitative variables were described as percentages, and quantitative variables were described as means and standard deviations or median, maximum, and minimum depending on their distributional characteristics in both groups. Kolmogorov–Smirnov test was used to assess the normal distribution of data.
A paired-sample t test was used for the comparative analysis of the repeated measurements taken from the POAG group; its corresponding non-parametric Wilcoxon test was used for non-normal datasets. All contrasts were bilateral with a significance level of 0.05.
For the comparative analysis of the different measurements between the POAG group and control group, the student’s t test for independent samples or its corresponding non-parametric U of Mann–Whitney test was used. All contrasts were bilateral with a significance level of 0.05.
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10

Evaluating MGIT 960 Mycobacterium Detection

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SPSS version 15.0 (IBM, Armonk, NY) was used for all data analysis. The Pearson chi-square test was used to analyze the proportions of “false-negative” (FN) and MGIT 960-positive MTB strains classified into different smear grades. The mean TTD between FN and MGIT 960-positive MTB isolates was compared with t-test. If the P value was less than 0.05, the difference was declared as significant.
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