Data were analysed using SPSS v14 (SPSS Inc., Chicago, IL, USA) statistical software package. The significance of the differences between proportions and means was tested using chi-square test and Student’s t-test/ANOVA respectively. Multiple groups were compared with post-hoc analysis using the fisher’s least significance difference (LSD) test. Unless otherwise stated age- and sex- standardized prevalence rates are presented throughout the manuscript. In all statistical analyses p < 0.05 was considered significant. Data were analysed using SPSS v14 (SPSS Inc., Chicago, IL, USA) statistical software package. Subjects were divided in to two groups based on the presence or absence of DR. A binary logistic regression analysis was performed in all patients with ‘presence of DR’ as the dichotomous dependent variable (0 = DR absent; 1 = DR present) and duration of diabetes (continuous), current smoking (binary), central obesity (binary) and peripheral neuropathy (binary) as the independent variables. The explanatory independent variables that were associated with the dependent variable in univariate analysis (p < 0.25) were selected to be included in the regression analysis. A similar binary logistic regression analysis with above dependant and independent variables was also performed separately for both males and females.
Spss v14
Manufactured by IBM
Sourced in United States
SPSS v14.0 is a statistical software package developed by IBM. It provides a comprehensive set of tools for data analysis, visualization, and modeling. The software is designed to assist users in processing and analyzing data from various sources, including surveys, experiments, and observational studies. SPSS v14.0 offers a range of statistical techniques, such as regression analysis, hypothesis testing, and multivariate analysis.
Automatically generated - may contain errors
Lab products found in correlation
Prism 6, by GraphPad (2 mentions)
Prism 7, by GraphPad (1 mentions)
Sigmaplot v12, by Grafiti LLC (1 mentions)
Origin v 2018, by OriginLab (1 mentions)
Design expert 6, by Stat-Ease (1 mentions)
Sas v8, by SAS Institute (1 mentions)
Excel 2003, by IBM (1 mentions)
Sigmastat, by Grafiti LLC (1 mentions)
Spss 18, by IBM (1 mentions)
Stata v10, by StataCorp (1 mentions)
Nuclear extract kit, by Active Motif (1 mentions)
Hss t3 c18 column, by Waters Corporation (1 mentions)
Acquity uplc h class system, by Waters Corporation (1 mentions)
105 protocols using spss v14
1
Diabetic Retinopathy Risk Factors Analysis
2
Sex Differences in SCM Intake
3
Factors Affecting Retinal Detachment
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Snellen's visual acuity was converted to equivalent logMAR units. Visual outcomes were categorized into three groups: improved, remained stable, and deteriorated. Two-proportion z-test was used to test the difference in proportion between two independent groups. Wilcoxon signed rank test was used to determine the difference in visual acuity at baseline and at final visit. Univariate binary logistic regression analysis was used to determine the risk factors for RD. Any P value less than 0.05 was considered as statistical significant. All statistical tests were performed using SPSS V 14.0.
4
Pharmacokinetic Analysis of Novel Compound
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The experimental results are presented as mean ± standard deviation values. The pharmacokinetic parameters were derived from a noncompartmental model analysis [60 ,61 (link)]. SPSS v14.0 (SPSS Inc., Chicago, IL, USA) was used to conduct analysis of variance, and multiple comparisons of variance were evaluated using the Scheffe post hoc test. A p value of < 0.05 was considered significantly difference.
5
Statistical Analysis of Measurement Data
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The measurement values in this study were analyzed using statistics software (SPSS v14.0, SPSS Inc., Chicago, IL). Results yielding a p value less than 0.05 were considered to be statistically significant.
6
Antioxidant and Enzyme Inhibitory Analysis
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The antioxidant and enzyme inhibitory activities results are given as mean ± standard deviation (S.D.). The results were statistically evaluated using the student t-test (α = 0.05). Pearson correlation coefficients were also calculated for total bioactive compounds and biological activities. Statistical analysis was carried out using SPSS v. 14.0 program (SPSS Inc, Chicago, IL, USA).
7
Nematode Lifespan Analysis Protocol
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Data were analyzed using Student’s t-test or analysis of variance (ANOVA), followed by Duncan’s test for group mean comparisons using the SPSS v.14.0 software (SPSS, Inc., Chicago, IL, USA). The differences in the lifespan of the nematodes between the groups were analyzed using log-rank test. p-values less than 0.05 were considered statistically significant.
8
Statistical Analysis of Experimental Data
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All calculations were performed with SPSS V.14.0 (SPSS Inc.). Comparisons between groups were performed using the Student’s t-test, χ2 test and Fisher’s exact test, and the data were expressed as mean±SD for continuous variables. A p value of <0.05 was considered statistically significant.
9
Investigating Factors Influencing Profitability
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Descriptive analyses and statistical testing were performed using SPSS, V.14.0 (SPSS) for Windows. Results are expressed as median (IQR) or frequency (%). We controlled data for risk and severity by exclusion as patients and therapies in intensive care are heterogenic, as studies have shown.18 (link) Differences between the adherence groups in terms of outcome parameters were tested using the univariate unpaired t-test and χ2 statistics for independent variables as appropriate with a p<0.05 regarded as significant.
In order to investigate the influencing factors in more detail, parameters that were found to be statistically significant on univariate analysis or out of discussion among the experts underwent stepwise multivariate analyses. We used multiple linear regression analyses to model the relationship between the independent variables and the outcome of profitability. Regression coefficients (95% CI) and the corresponding p values were calculated for each factor. Testing the dataset for outliers was performed using the cook distance test, based on the model. The test did not indicate the need to dismiss cases from the sample. Due to an exploratory character of the research, no adjustments for multiple testing were made.
In order to investigate the influencing factors in more detail, parameters that were found to be statistically significant on univariate analysis or out of discussion among the experts underwent stepwise multivariate analyses. We used multiple linear regression analyses to model the relationship between the independent variables and the outcome of profitability. Regression coefficients (95% CI) and the corresponding p values were calculated for each factor. Testing the dataset for outliers was performed using the cook distance test, based on the model. The test did not indicate the need to dismiss cases from the sample. Due to an exploratory character of the research, no adjustments for multiple testing were made.
10
Examining Smoke Exposure and Depression
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Descriptive statistics were used to examine the distribution of demographic and social characteristics. A χ2 test was used to estimate the difference in the existence of depression by current smoke and secondhand smoke exposure. Multiple logistic regression analysis was performed to identify the association between smoke exposure and depression. Age, sex, sociodemographic and depression variables that showed a significant difference in a χ2 test and t test were adjusted for the analysis. The adjusted OR and corresponding 95% CIs were calculated. All p values were considered to be statistically significant at less than 0.05. All estimates were calculated based on sample weights, which were evaluated by taking into consideration the sampling rate, response rate, sex, school type and grade proportions of the reference population. Of whom 4.5% were missing, and hence missing data were already reflected to response rate when calculating weight. The analysis was adjusted for the complex sample design of the survey.20
21 All analyses were conducted using SPSS V.14.0.
21 All analyses were conducted using SPSS V.14.0.
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