The SPSS statistical software package version 22.0 (IBM Corp., Armonk, NY) was used for all analyses. The AE and CON groups were compared on demographic variables using chi-square (ethnicity, handedness, race and sex) and standard analysis of variance (ANOVA) techniques (age, GCA, and socio-economic status [SES], as measured by the Hollingshead 4-factor index). Three separate MANOVAs with a 2 (Exposure History: AE, CON) × 2 (Age Group: child, adolescent) × 2 (Sex: male, female) design were used to measure: (1) neuropsychological performance (NEPSY-II and DAS-II), (2) psychopathology (CBCL), and (3) adaptive functioning (VABS-II). Behavioral data were analyzed by two separate MANOVAs because the assessment tools measure two different aspects of functioning, and the CBCL, which measures psychopathology, is normed by age and sex, while the VABS-II, which measures adaptive functioning, is only normed by age. Both the NEPSY-II and the DAS-II are normed by age only, so the neuropsychological data was analyzed with one MANOVA. Wilks’ criterion (Λ) was used as the omnibus test statistic. A Bonferroni correction was used to control for Type 1 error (.05/3), so results were considered to be significant at an alpha of p < .017 and marginally significant at an alpha of .017 ≤ p < .023 (.07/3). Significant interactions were followed up with univariate simple effects tests.
Spss statistical software package version 22
Manufactured by IBM
Sourced in United States
SPSS Statistics is a software package used for statistical analysis. Version 22.0 includes a range of data management and statistical analysis capabilities. The software provides tools for data manipulation, exploration, modeling, and reporting.
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Lab products found in correlation
32 protocols using spss statistical software package version 22
1
Neurodevelopmental Outcomes in Exposure Groups
2
Statistical Analysis of Patient Data
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In the descriptive analysis of the data, patient characteristics were expressed as percentages for the qualitative variables and mean ± SD for the quantitative variables. The chi‐square test of Pearson and Fisher's exact test were used to compare the proportions of the qualitative variables. p‐Values <.05 were considered statistically significant. All statistical analyses were performed using the IBM SPSS statistical software package version 22.0 (SPSS Inc.).
3
Statistical Analysis of Qualitative and Quantitative Data
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All statistical analyses were performed using the IBM SPSS statistical software package, version 22.0 (SPSS Inc.; New York, United States). The qualitative variables were expressed as percentages and the quantitative variables as mean ± standard deviation. The Chi-square test of Pearson and Fisher’s exact test was used to compare the proportions of the qualitative variables. The
p-values <0.05 were considered statistically significant.
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All statistical analyses were performed using the IBM SPSS statistical software package, version 22.0 (SPSS Inc.; New York, United States). The qualitative variables were expressed as percentages and the quantitative variables as mean ± standard deviation. The Chi-square test of Pearson and Fisher’s exact test was used to compare the proportions of the qualitative variables. The
p-values <0.05 were considered statistically significant.
4
Cycloplegic Astigmatism Characteristics
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SPSS statistical software package, version 22.0 (IBM Corporation, Armonk, NY, USA) was used for data analysis. Due to the high correlation between the results of the two eyes (r = 0.741), we only considered information related to the right eye in our analyses.
We have used cycloplegic SE in our analysis. The mean and standard deviation of different types of astigmatism were determined according to age and sex. Simple and multiple linear regression were used to investigate the effect of each variable on the ORA and CA.
If the relationship was not linear and the data were u-shaped, one group was considered the reference group against which other groups were compared.
We have used cycloplegic SE in our analysis. The mean and standard deviation of different types of astigmatism were determined according to age and sex. Simple and multiple linear regression were used to investigate the effect of each variable on the ORA and CA.
If the relationship was not linear and the data were u-shaped, one group was considered the reference group against which other groups were compared.
5
Feasibility of Lung Ultrasound for Postoperative Complications
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We included as many consecutive patients as possible in the study period. We planned to include more than 90 patients to detect around 30 PPCs based on incidence rates of PPCs after surgery [16 (link)]. Results of this study will be used to plan a larger study on the effects of LUS on patient outcome after major abdominal surgery. We performed statistical data analyses using SPSS statistical software package version 22.0 (IBM, New York, NY, USA). Feasibility was reported as percentage of patients in which LUS was possible. Detection rates of PPCs during the study period were reported as frequencies. A PPC could only develop once. For example, if a pleural effusion was detected on POD1, it could not be scored again on POD2. However, a patient could develop more than one PPC during the study period and during 1 day. In addition, detection rates were compared according to both imaging modalities. Furthermore, an aggregated analysis was performed to compare the detection of PPCs in patients who had both; CXR and LUS were performed the same day during the study period. Relative risk was calculated comparing PPC detection with LUS and CXR. Discordant observations were compared for PPCs detected with LUS and CXR.
6
Serum Fibrosis Indices Diagnostic Accuracy
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Continuous variables were presented as median (50th percentile) and interquartile range (25th and 75th percentiles). All statistical analyses were performed using the SPSS statistical software package version 22.0 (IBM, Armonk (HQ), NY, USA). The diagnostic accuracy of the serum fibrosis indices (sensitivity, specificity, PPV, NPV and accuracy) was determined using the area under receiver operating characteristic curves. p values < 0.05 were considered to indicate statistical significance.
7
Quantitative Protein Expression Analysis
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All data are presented as the mean ± standard deviation (SD) of the assigned number of independent experiments or number of mice. Prior to significance testing, the normality of the data and the equality of group variance were confirmed using the Shapiro-Wilk and Levene’s tests respectively. Where necessary, normality was achieved using logarithmic transformation. For single comparisons, values of p were determined using Student’s t-test. For multiple comparisons, values of p were determined using one-way analysis of variance (ANOVA) with Tukey’s (equal variance) or Dunnett’s T3 (unequal variance) post-hoc analysis. Statistical analysis was performed using SPSS statistical software package version 22 (IBM, New York, USA). Significance was defined when p < 0.05.
8
Factors for Contrast-Induced Acute Kidney Injury
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Continuous variables were expressed as median and interquartile range, and Kruskal-Wallis test was used to evaluate differences among groups. Categorical variables were shown as count and percentage, and comparisons among groups were performed with Chi-square test or Fisher's exact test as appropriate. Univariate and multivariate logistic analysis was used to evaluate the risk factors for CI-AKI. A two-sided P < 0.05 was considered to indicate statistical significance. All tests were performed using the IBM SPSS statistical software package version 22 (SPSS Inc., Chicago, Illinois, USA).
9
Mortality Risk Factors Analysis
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Statistical analysis was performed using the IBM SPSS statistical software package version 22 (IBM Corp., Armonk, NY, USA). Because this study group was small, continuous variables were accepted as nonnormally distributed and were described as median and interquartile ranges. Categorical variables were presented as frequencies and percentages. Patients were divided into 2 groups as survivors and nonsurvivors. The Mann-Whitney U test was used to compare the continuous variables between the 2 independent groups. The Chi-square test was used to compare categorical variables. Among the variables that indicated statistically significant differences regarding mortality, the logistic regression analysis was performed to determine the variables that were independently related to mortality. After the determination of independent risk factors for mortality, ROC (Receiver Operating Characteristic) curve analyses were performed.
10
Comparative Analysis of Cell Viability
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All data are presented as the mean ± standard error of the mean (SEM) of the assigned number of independent experiments. The normality of all data was assessed using histograms and Q-Q plots and data transformations were applied where appropriate. For single comparisons, values of P were determined using a Student's t-test. For multiple comparisons, P-values were determined using one-way analysis of variance (ANOVA) with Tukey's or Dunnett's T3 post-hoc analysis or, where the data was not normally distributed, Kruskal-Wallis ANOVA with Dunns post-hoc analysis. All statistical tests were performed using SPSS statistical software package version 22 (IBM, Armonk, NY, USA). Differences were considered significant when P<0.05.
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