The central focus of this study was to describe the levels of functioning across various domains. Descriptive statistics were used to present demographic characteristics of the study population and the levels of functioning. Associations between scores in the three health domains and the frailty stages were analysed using Kendall’s tau for nominal and ordinal variables, and analyses of variance (ANOVA) for all other variables (P < 0.05).These associations were also studied separately for men and women, as older women are more likely to be frail. Where available, missing data for all of the included instruments were handled as proposed by the original authors. Fried and colleagues excluded people with three or more missing frailty components. Missing data with respect to the Fried criteria in our study were handled more strictly than originally proposed by the authors. To reduce the number of misclassifications, only one missing value was allowed when a person had a valid Fried score of 0–2. If a person had a valid Fried score of 3 points or more, two missing values were allowed, because this would not cause misclassification. The analyses were performed using IBM SPSS Statistics software version 19.
Spss statistics software version 19
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SPSS Statistics software version 19 is a comprehensive and integrated statistical analysis tool designed for data management, analysis, and reporting. It provides a wide range of advanced analytical techniques to help researchers, analysts, and decision-makers gain valuable insights from their data.
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Lab products found in correlation
139 protocols using spss statistics software version 19
1
Frailty Levels and Health Domains
2
Analyzing Stress and Drug Effects on Animal Physiology
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Weight of animals was analyzed using repeated measures two-way analysis of variance (ANOVA) with the stress (control, JVS) and the drug treatment (no FLX, FLXjuv, FLXadlt) as factors. Fluid intake was analyzed separately for the two treatment periods using repeated measures two-way ANOVA with the stress (control, JVS) and the drug treatment (water, FLX) as factors.
Behavioral differences in the EPM were first analyzed by using two-way ANOVA with the stress (control, JVS) and the drug treatment (no FLX, FLXjuv, FLXadlt) as factors, followed by Bonferroni post hoc tests for the drug treatment factor when needed. Then, individual behavioral profiling was applied and the distribution of affected vs. unaffected populations was calculated by using Chi-squared test for goodness of fit.
All tests were selected after confirming data meet the assumptions of the tests. Data were analyzed using the IBM SPSS Statistics Software version 19 (IBM, Armonk, NY, USA).
Behavioral differences in the EPM were first analyzed by using two-way ANOVA with the stress (control, JVS) and the drug treatment (no FLX, FLXjuv, FLXadlt) as factors, followed by Bonferroni post hoc tests for the drug treatment factor when needed. Then, individual behavioral profiling was applied and the distribution of affected vs. unaffected populations was calculated by using Chi-squared test for goodness of fit.
All tests were selected after confirming data meet the assumptions of the tests. Data were analyzed using the IBM SPSS Statistics Software version 19 (IBM, Armonk, NY, USA).
3
Statistical Analysis of Experimental Groups
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The statistical analysis among the different groups was conducted using IBM SPSS Statistics software, Version 19 (IBM Corporation, Armonk, NY, USA). p < 0.05 was considered statistically significant.
4
Postoperative Hct Changes Analysis
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The statistical analysis was performed with IBM SPSS statistics software version 19 (IBM Co, Armonk, NY, USA). The measurement data are shown as the mean ± standard deviation, and the qualitative and ordinal data were demonstrated as frequency distributions. The independent sample t-test was applied to compare post-operative Hct changes between two different groups. One-way ANOVA analysis was applied to compare post-operative Hct changes among three or more groups. If the test of homogeneity of variance was inappropriate, the Kruskal-Wallis test was applied for multiple independent samples of non-parametric tests. Pearson’s correlation coefficient was used to explore the correlation between continuous variables. Multiple linear regression was used to explore the predictors of post-operative Hct with a stepwise regression strategy while controlling for smoking, alcohol drinking, anaemia and NNIS. Throughout data analysis, P < 0.05 was considered statistically significant.
5
Reliability Analysis of SHERPA in Older Patients
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Intra- and inter-reliability of SHERPA was analysed in an independent sample of thirty older patients, enrolled prospectively. The only exclusion criterion was the impossibility of interview because of clinical or cognitive status. Researchers (IDB, PC) were blinded to previous SHERPA evaluation of the patient and SHERPA scores were calculated after the end of the protocol. We used IBM SPSS Statistics software, version 19. Intraclass correlation coefficients (ICC) and their 95% confidence interval (IC95%) were calculated using a two-way random effects model [19 (link)].
6
Statistical Analysis of Biological Experiments
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The statistical analysis was performed using the IBM SPSS statistics software, version 19 (ibm.com/support/pages/spss-statistics-190-fix-pack-1). The results were expressed as mean ± standard errors. Depending on applicability, the t-test (paired and unpaired) and One-way ANOVA test were used, with Bonferroni post hoc analysis of differences between groups. The χ2 test was used for the analysis of non-parametric data in 2 × 2 tables. The Pearson and Spearman tests were used for correlation analyses using a threshold of p = 0.05.
7
Statistical Analysis of Experimental Data
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Cluster 3.0 and Tree-view software packages were used for cluster analysis and heatmap drawing. All statistical tests were two-sided, with a P < 0.05 considered to be statistically significant. Statistical analysis was performed by using IBM SPSS Statistics software (version 19). Adobe Illustrator CS6 and GraphPad Prism 7 were employed for figure editing.
8
Biomarker Profiling for Treatment Outcomes
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Protein, mRNA and miRNA expression (positive vs negative) were correlated with treatment outcome according to the cohorts of LR and PR. Survival probabilities were assessed by the Kaplan-Meier method. Cox proportional hazard models were used to identify predictors of treatment outcomes. To determine their ability to discriminate the two populations we sequentially performed unpaired tTest, ROC analyses and Kaplan-Meyer distributions with LogRank test. For all statistical tests, an a priori significant level of α=0.05 was assumed.
Efficacy end points included ORR, OS and PFS, assessed by investigators using Response Evaluation Criteria in Solid Tumours v1.1 [34 (link)]. The AEs were recorded regularly and graded according to Common Terminology Criteria for Adverse Events (CTCAE) v4.0. SPSS Statistics© software version 19 (IBM, Armonk, NY) was used for statistical analysis.
Efficacy end points included ORR, OS and PFS, assessed by investigators using Response Evaluation Criteria in Solid Tumours v1.1 [34 (link)]. The AEs were recorded regularly and graded according to Common Terminology Criteria for Adverse Events (CTCAE) v4.0. SPSS Statistics© software version 19 (IBM, Armonk, NY) was used for statistical analysis.
9
Dental Surface Analysis and Fluoride Adsorption
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The statistical analysis was performed by SPSS Statistics software, version 19 (IBM Corp., New York, NY) and the level of significance was set at p < .05.The mean abraded depth and surface roughness (Ra) were analyzed using the Kruskal–Wallis test followed by the Dunn’s multiple comparison test, as the assumption of equal variance was not met. To analyze results from the fluoride adsorption study, one-way ANOVA was performed at time point 0 and 24 h. The pH values were analyzed using one-way ANOVA followed by the Tukey’s post-hoc test.
10
Clinical Significance of KRAS Mutations
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All statistical analyses were performed using IBM SPSS statistics software, version19 (IBM Corporation, New York, NY, USA). Either the χ2 test or Fisher's exact test was used to analyze the association between KRAS mutations and the patients' clinicopathological characteristics. Relapse-free survival (RFS) was defined as the period from the completion of surgery to the date of documented evidence of disease recurrence. The end of the observation period was March 31, 2016, and patients without disease recurrence were censored at their last follow-up visit. Survival curves were calculated using the Kaplan-Meier method, and differences between the groups were tested using the log-rank test. The Cox proportional hazards model was used for multivariate survival analysis. Statistical significance was set at p<0.050.
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