First, collected data were processed through data input, data cleansing, and data reversing [41 ]. Second, frequencies, percentages, maximum score, minimum score, mode, median, mean, and standard deviation were used to describe the demographic characteristics and the participants’ habits and attitudes regarding internet use and video gaming [52 (link)]. To facilitate the analysis of the current and favorite video games played, the entries were recategorized into different game genres. We utilized an extensive gaming archive [56 ] to sort the entries into 10 mutually exclusive game genres. Lastly, a two-tailed independent t test was used to describe the possible differences in the normally distributed variables of the gaming attitudes. The Pearson’s correlation coefficient was used to quantify the linear relationship between the categories of the gaming attitudes. Statistical significance was established at P=.05. For the dimensions of the categories of the gaming attitudes that were the most intercorrelated, principal analysis with 3 methods of rotation (varimax, equamax, and promax) was used to confirm the convergence of the 9 categories of gaming attitudes into fewer principle factors for easy interpretation. The SPSS software for Windows 22.0 (IBM Corp) was used for the data analysis.
Spss 22 software for windows
Manufactured by IBM
Sourced in United States
SPSS 22 is a statistical software package for Windows developed by IBM. It provides a range of analytical tools and techniques for data analysis, including descriptive statistics, regression analysis, and data mining. The software is designed to help users extract insights from data and make informed decisions.
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Lab products found in correlation
19 protocols using spss 22 software for windows
1
Analyzing Gaming Attitudes and Behaviors
2
Ultrafast PCR for Canola Events
3
Peer Bullying and Adolescent Obesity
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Statistical evaluations were made using Statistical Package for the Social Sciences (SPSS) software for Windows 22.0 (IBM Corp.; Armonk, NY, USA). The normality of the distribution was evaluated by the Shapiro-Wilk test. To compare the data obtained from the obesity and control groups who participated in the study, the independent sample t test was used for normally distributed data and the Mann-Whitney U test was used for non-normally distributed data. Categorical data were compared using the chi-square test. Descriptive statistical values including mean and standard deviation were expressed for continuous data, and median and interquartile range (IQR) were expressed for nonparametric data. To evaluate the relationship between the sociodemographic data and scale scores of the obese adolescents and controls, Pearson’s correlation analysis was used for parametric data, and Spearman’s correlation analysis was used for nonparametric data. Logistic regression analysis was conducted to evaluate the factors affecting peer bullying. A P value of < .05 was considered statistically significant.
4
Postop Inflammation and Pain Assessment
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Statistical analysis was performed using descriptive and analytical statistics. Categorical variables were compared using the chi-squared test. The normality of distribution was assessed using the Kolmogorov-Smirnov test. Continuous variables not normally distributed were compared using the Mann-Whitney U test. As an additional analysis, the receiver-operating characteristic (ROC) curve with the calculation of the area under the curve (AUC) was used to indirectly assess the possible association of amino acids, lidocaine, and magnesium use with the levels of the postoperative inflammatory and pain parameters. SPSS software for Windows 22.0 was used. P<0.05 was considered statistically significant.
5
Effectiveness of Dry Needling: A Pilot Study
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The data analysis was carried out using SPSS software for Windows 22.0 (SPSS Inc., Chicago, IL). We calculated the mean and standard deviation (SD) for continuous variables and number and percentage for categorical variables. The Kolmogorov–Smirnov (KS) test was employed to assess whether the variables were normally distributed. One-way repeated measure of analysis of variance (ANOVA) with time as within-subject factor measured at three time points was used. Bonferroni adjustments were applied for post hoc paired comparisons of testing time points. Mauchley's test was used to analyze the homogeneity of variances. The paired t-test was used to analyze the changes of FRI scores. Cohen's d was calculated to determine the magnitude of the DN effect defined as small <0.50, moderate 0.50–0.80, and large ≥0.80 [20 (link)]. P ≤ 0.05 was interpreted as statistically significant.
Before we began the current pilot study, we conducted a power analysis for the future larger randomized, controlled trial. With ANOVA, repeated measure, between factors as the statistical test, effect size of 0.5, significance level of 0.05, power 0.80, two groups (DN and sham DN), and 3 measurements, a total sample size of 24 patients would provide adequate power to detect meaningful differences between groups.
Before we began the current pilot study, we conducted a power analysis for the future larger randomized, controlled trial. With ANOVA, repeated measure, between factors as the statistical test, effect size of 0.5, significance level of 0.05, power 0.80, two groups (DN and sham DN), and 3 measurements, a total sample size of 24 patients would provide adequate power to detect meaningful differences between groups.
6
Predictive Markers for Distant Metastasis
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Comparison of qualitative variables between groups was performed using the chi-square or Fisher’s exact test. The diagnostic sensitivity and the specificity for each of the markers individually, as well as in different combinations, were calculated. Using a logistic regression model, univariate analysis was conducted and odds ratios were estimated to assess predictive markers for distant metastasis. Two-sided P-values of less than 0.05 were considered statistically significant. Statistical analyses were performed using IBM SPSS 22 software for Windows (IBM Corp, New York, USA).
7
Statistical Analysis of Survival Outcomes
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The Mann-Whitney (MW) U test, one-way ANOVA, two-sample t-test, x2 test, and Pearson's or Spearman's correlation test were used to analyze the significance of differences among the variables examined. Overall survival times were measured from the date of surgery to the date of death or last follow-up visit. Recurrence-free survival was defined as the time from surgery to the first clinical, radiological, and/or histological evidence of recurrence in intraperitoneal or distant organs. Patient survival rates were determined using the Kaplan-Meier method, and differences in survival rates were compared using the log-rank test. Multivariate analysis was performed using the Cox proportional hazards model. A two-sided P-value <0.05 was considered statistically significant. Statistical analyses were performed using IBM SPSS 22 software for Windows (IBM Corp, Somers, New York).
8
Evaluating lncRNA Expression in Survival
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High or low expression of lncRNAs was determined using Youden's index for survival. Pearson's χ2 test or Fisher's exact test was used to compare differences between variables, and the Spearman coefficient was used for correlation analysis. Overall survival curves were plotted using the Kaplan–Meier method and compared using the log-rank test. Multiple linear regression analysis was used for probing the interactions of markers. A P-value <0.05 was considered statistically significant. Statistical analyses were performed using IBM SPSS 22 software for Windows (IBM Corp, Somers, NY, USA).
9
Longitudinal Trends in Bullying Behavior
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Statistical analysis was conducted in the IBM SPSS 22 software for Windows. For the trend, a logistic regression analysis (Enter method) was used with a dependent variable -who bullied someone at least once or more and who were bullied at least once or more -and an independent categorical variable, which was the year that the survey was completed (1994, 1998, 2002, 2006, 2010, 2014) , with 1994 as the reference year.
10
Statistical Analysis of VLP Binding
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Statistical analyses were performed using the SPSS 22 software for Windows (SPSS, Inc., Chicago, IL, USA). Student’s t-tests were performed on the VLPs binding block assay, and the nonparametric Mann-Whitney U tests were performed on the in vivo zebrafish model. Significant differences were considered when p was <0.05.
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