Statistical analyses were performed using Statistical Package for the Social Sciences (IBM SPSS Advanced Statistics 24.0; IBM Corp, Armonk, NY, USA). Categorical variables are presented as a numerical value (n) with percentages (%), continuous variables with a normal distribution were reported as means and standard deviations (SDs), and skewed distribution (non-Gaussian) data are reported as medians with interquartile ranges. Characteristics between patients with successful and unsuccessful measurements were compared using an unpaired sample t test for continuous data, Mann-Whitney U test for skewed distribution data or the χ2 test for categorical data. A p value of less than 0.05 was considered statistically significant.
Spss advanced statistics 24
Manufactured by IBM
Sourced in United States
SPSS Advanced Statistics 24.0 is a statistical software package that provides advanced analytical capabilities for users. The software offers a range of statistical techniques, including regression analysis, multivariate analysis, and time series analysis, among others. SPSS Advanced Statistics 24.0 is designed to assist users in conducting complex data analysis and generating insights from their data.
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Lab products found in correlation
6 protocols using spss advanced statistics 24
1
Statistical Analysis of Measurement Outcomes
2
Analyzing Health Outcomes with Descriptive Statistics
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Descriptive statistics were used to analyze patient characteristics and changes in health outcomes using Statistical Package for the Social Sciences (SPSS) (IBM SPSS Advanced Statistics 24.0, Armonk, NY, IBM Corp). Categorical variables were presented as frequencies (n) with percentages (%). Normally distributed continuous variables were reported as means with standard deviations (SDs). Medians with interquartile ranges (IQR) were reported for continuous variables with skewed distribution.
Graphs were produced using Plotly (Plotly Technologies Inc., Montreal, Québec, Canada) (box plots) and GraphPad Prism version 9.0.2 for Windows (GraphPad Software, San Diego, California USA) (all other graphs).
Graphs were produced using Plotly (Plotly Technologies Inc., Montreal, Québec, Canada) (box plots) and GraphPad Prism version 9.0.2 for Windows (GraphPad Software, San Diego, California USA) (all other graphs).
3
Macular Hemodynamics in Thyroid Eye Disease
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Because of the high correlation coefficients of parameters between left and right eyes, only the data from right eyes were analyzed. The normal distribution of data was assessed with the Shapiro–Wilk test. Normally distributed data were presented as means with standard deviations and non-normally distributed data were presented as median with quantiles. Chi-square analysis was used for categorical data. The influence of age, eyelid aperture, IOP, TAO grade, and CAS on FAZ and macular blood flow in the TAO group were analyzed using Spearman correlation test and multiple linear regression analysis. The effects of FAZ and retinal blood flow on BCVA in the TAO group were analyzed using linear regression. The differences in FAZ and retinal blood flow between subjects (control group and TAO subgroups) were analyzed using Kruskal–Wallis H test. The sample size was analyzed using the Power Analysis and Sample Size (PASS) (PASS 15.0.5, NCSS, LLC). Data analyses were performed using the Statistical Package for the Social Sciences (SPSS) (IBM SPSS Advanced Statistics 24.0, Armonk, NY, IBM Corp). Results were considered significant at the P < 0.05 level.
4
Factors Associated with Self-Harm Behaviors
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Participants’ sex, age, socioeconomic status, academic performance, Internet usage time, and experiences of bullying, child abuse, and self-harm were analyzed using descriptive statistics. To compare the relationship between self-harm experience and sex, experience of school violence, and experience of child abuse, Pearson’s chi-squared test (χ2) was used. Age, socioeconomic status, academic grades, and Internet usage time were analyzed as ordinal variables to determine whether they showed trends according to the presence or absence of self-harm experiences using the likelihood ratio test. The variables showing associations with self-harm from the above analysis were used as independent variables for multinomial logistic regression.
Differences in response styles to depressed mood and scores of emotion regulation difficulties between the self-harm and non-self-harm groups were assessed using independent sample t-tests. The statistical significance level was set at a twotailed p<0.05, and all analyses were conducted using IBM SPSS Advanced Statistics 24.0 (IBM Corp., Armonk, NY, USA).
Differences in response styles to depressed mood and scores of emotion regulation difficulties between the self-harm and non-self-harm groups were assessed using independent sample t-tests. The statistical significance level was set at a twotailed p<0.05, and all analyses were conducted using IBM SPSS Advanced Statistics 24.0 (IBM Corp., Armonk, NY, USA).
5
Assessing Group Differences in ASC
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We used the Student's t‐test and the Mann–Whitney U‐test to compare group differences and to assess relations among ASC, psychological traits, personality traits, and psychiatric symptoms.
All analyses were conducted usingspss 24 Advanced Statistics (IBM, Armonk, NY, USA) for Mac OS with two‐sided alpha = 0.05.
All analyses were conducted using
6
Hikikomori Risk Factors in ASD
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We used unpaired Student's t-test and Mann-Whitney U-test to compare the group difference. Next, we used stepwise binomial logistic regression to examine associations between candidate predictor variables (self-administered rating scales including subscales and blood test results) and presence of co-occurring social withdrawal. All analyses were conducted using IBM SPSS 24 Advanced Statistics for Mac OS with two-sided alpha = 0.05. The logistic regression model was used to calculate the adjusted odds ratio (OR) with 95% confidence interval (CI) for risks of hikikomori associated with ASD. The multivariate logistic regression model was performed with adjustments for all potential confounding factors as listed in Tables 1 –3 .
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