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Statistics for windows version 22

Manufactured by IBM
Sourced in United States

Statistics for Windows, Version 22.0 is a software package that provides statistical analysis tools for data processing and visualization. The software is designed to run on Windows operating systems.

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Lab products found in correlation

8 protocols using statistics for windows version 22

1

Evaluating Restorative Material Survival

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The IBM SPSS (Software Package for the Social Sciences) Statistics for Windows, Version 22.0, Armonk, NY, USA: IBM Corp. June 2018 was used for statistical analysis. Repeated measures of ANOVA for intragroup comparison along with post-hoc Bonferroni test and independent-sample t-test for intergroup comparison was carried out. Life table analysis for survival analysis of the restorative materials in both techniques and the cost-effectiveness ratio (CER) was calculated.
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2

Analyzing Gene Expression in Northern Pike Livers

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Data were analyzed with IBM Statistics for Windows, version 22.0 (IBM Corp., Armonk, N.Y., USA). A non-parametric Kruskal–Wallis test was performed to determine differences among parks sampled, with a Dunn’s post hoc test used to determine differences in gene expression in the livers of northern pike from among the parks. Linear regressions were used to determine the relationship between Se, MeHg, THg, and between gene expression and %MeHg. Spearman pairwise correlations were conducted between normalized gene expression, Se, MeHg, and THg. Due to wedge shaped distributions, quantile regression analysis of genes relative to the molar concentrations of THg and Se was conducted using the program Blossom (version 2005.04.02) [41 (link)]. Gene expression outliers were determined if standard deviations were ±2 from the mean. Statistical significance was evaluated at p < 0.05.
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3

Statistical Analysis of Experimental Data

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Statistics for Windows Version 22 (IBM, Armonk, NY, USA). All values are presented as means±SEM. Differences during the followup were investigated by paired-sample t-test. Independent sample ttest was used to compare parameters between groups. All differences with p-values lower than 0.05 were considered statistically significant.
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4

Product-Related Injury Surveillance in Australia

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The data specifications and classification systems for the state-based injury surveillance emergency presentation data, national hospitalization data, and national coronial data systems were reviewed to identify relevant codes and data fields to identify opportunities for identification of any of the products with a mandatory safety standard. For only the product where data were available across two of the three systems, descriptive analysis was conducted to examine the frequency of presentations over time, age and sex patterns, and mechanism of injuries and types of injuries sustained. As the first aim was to investigate how effectively information regarding product-related injuries is able to be captured within Australian health and coronial data, the authors chose to only report the extent of injuries/deaths (the second aim) for those cases where at least two data sources captured data pertaining to these products. Statistical analysis was conducted using IBM Statistics for Windows, Version 22 (Armonk, NY, USA) [10 ].
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5

Survival Analysis of EBV Status

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Chi-square tests were performed to compare EBV-positive and EBV-negative patients. Hazard ratios (HR) were derived from Cox proportional hazard regression models adjusted for personal (age, sex, BMI) and tumor-related (EBV status, tumor stage, topological localization) covariates. Cumulative survival curves were constructed by the Kaplan-Meier method. A two-sided p-value less than 0.05 was considered statistically significant. Statistical analysis was performed using SPSS 22 software (IBM Corp. Released 2013. IBM Statistics for Windows, Version 22.0, Armonk, NY: IBM Corp.).
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6

Anticoagulant Therapy Comparative Analysis

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Categorical variables were expressed as absolute frequency (n) and relative frequency (%). Continuous variables were expressed as measures of central tendency (mean and median) and dispersion (standard deviation and interquartile range). Categorical variables were compared using the χ2 test or the Fisher exact test, as appropriate. When 2 means were compared, the t test (parametric) or the Mann-Whitney test (nonparametric) was used, as appropriate, and 3 means were compared using analysis of variance (parametric) or the Kruskal-Wallis test (nonparametric), as appropriate. Time-to-event (mortality, total bleeds, and admissions to the intensive care unit) curves were constructed using an unadjusted Kaplan-Meier method. The log-rank test was used to compare outcomes according to anticoagulant therapy, dose of edoxaban, and dose of LMWH. A Cox regression model adjusted for potential confounders was constructed. Age, sex, hypertension, diabetes, prior myocardial infarction, and heart failure were included as potential cofactors, and log-likelihood was calculated. Effect sizes were presented as hazard ratio and 95% confidence interval. Statistical significance was set at 0.05 for all the tests. The data were analyzed using the statistical package IBM Statistics for Windows, Version 22.0 (IBM Corp).
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7

Statistical Analysis of Experimental Data

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Was performed using SPSS software Statistics for Windows, Version 22.0 (Chicago:
SPSS Inc, Chicago, Illinois, USA) and we used the Independent samples t-test,
Mann-Whitney, and Chi2 for the data analysis.
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8

Evaluating Incision Complications in Surgery

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Was performed using SPSS software Statistics for Windows, Version 22.0.(Chicago: SPSS Inc, Chicago, Illinois, USA). Chi-Square test was used to compare nominal variables. The odds-ratio was used in order to evaluate complications with or without incising external oblique aponeurosis. p<0.05 was considered significant.
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