SPSS statistical software, version 17, was used for data analysis. Common statistics were applied in order to estimate the significance of the results. Chi-square test, Mann-Whitney nonparametric test, and Fischer's exact test were used as appropriate. Differences were considered to be significant if P < 0.05.
Spss statistical software version 17
Manufactured by IBM
Sourced in United States
SPSS is a statistical software package developed by IBM. Version 17.0 provides a suite of tools for data analysis, including capabilities for data management, statistical modeling, and visualization. The software is designed to help users analyze and interpret data from a variety of sources.
Automatically generated - may contain errors
Lab products found in correlation
Prism 5, by GraphPad (2 mentions)
Epics xl mcl, by Beckman Coulter (1 mentions)
Lambda 850 spectrophotometer, by PerkinElmer (1 mentions)
Nexion 300x, by PerkinElmer (1 mentions)
Infinite m200 pro, by Tecan (1 mentions)
Chemidoc xrs imaging system, by Bio-Rad (1 mentions)
Avance 400 spectrometer, by Bruker (1 mentions)
Design expert software, by Stat-Ease (1 mentions)
Trizol reagent, by Thermo Fisher Scientific (1 mentions)
R software version 3, by R Project for Statistical Computing (1 mentions)
155 protocols using spss statistical software version 17
1
Statistical Analysis of Research Data
2
Comparative Analysis of Sexual Desire
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The independent t test was used to compare means of continuous variables between case and control subjects. Changes in sexual desire levels as a function of time were assessed using repeated-measures analysis of variance (ANOVA) with mixed linear modeling. All comparisons of sex, marriage status, and depression history were conducted using the chi-square test, with Yates’ correction when appropriate. All probabilities were two-tailed. Statistical significance was set at p<0.05. All analyses used the SPSS statistical software version 17 (SPSS Inc., Chicago, Illinois, USA).
3
Reliability and Scapular Dyskinesis Assessment
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Data were analyzed using SPSS statistical software version 17. Significance level was considered at 0.05. Demographic characteristics were described in mean and standard deviation. Intra Class Correlation (ICC), Standard Error of Measurement (SEM), and Minimum Detectable Change (MDC) were used to assess the relative and absolute reliability of the study measurements. Kolmogorov-Smirnov test was used to assess the distribution of the variables. To assess the equality of variances for a variable calculated for the 2 groups, Levene’s test was used. To investigate group differences, independent t test was used for the quantitative variables. Also, chi-square test was used to determine whether there was a significant difference between the scapular dyskinesis prevalence in individuals with or without RSP. Significance level was set at 0.05.
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Data were analyzed using SPSS statistical software version 17. Significance level was considered at 0.05. Demographic characteristics were described in mean and standard deviation. Intra Class Correlation (ICC), Standard Error of Measurement (SEM), and Minimum Detectable Change (MDC) were used to assess the relative and absolute reliability of the study measurements. Kolmogorov-Smirnov test was used to assess the distribution of the variables. To assess the equality of variances for a variable calculated for the 2 groups, Levene’s test was used. To investigate group differences, independent t test was used for the quantitative variables. Also, chi-square test was used to determine whether there was a significant difference between the scapular dyskinesis prevalence in individuals with or without RSP. Significance level was set at 0.05.
4
Comprehensive Statistical Analysis of FNAB and Elastography
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SPSS statistical software version 17 (SPSS Inc, Chicago IL, USA) was used for the descriptive analysis of all the parameters which includes the biodata, results of the FNAB as well as the elastography. Cross tabulation was used in analysis of association between two or more parameters. Correlational analysis was also used to show association as well as relationship between them to discover if dependency or independency can be seen. Chi square as well as ANOVA were also used for inferential statistics. SPSS statistic was also used to draw the ROC curve for strain ratio in order to determine the cutoff point for determination of malignancy and benignity of the tumor.
5
Bayesian Latent Class Modeling for Diagnostic Test Accuracy
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Data was entered and analyzed using SPSS® statistical software version 17. Descriptive analysis was done using percentages. The MICE tool (Modelling for Infectious Diseases Centre, Mahidol-Oxford Research Unit, Thailand [http://mice.tropmedres.ac/home.aspx ]) was used for Bayesian latent class modeling. The use of Bayesian latent class models to determine the accuracy of diagnostic tests where the gold standard is imperfect has been described elsewhere [7 (link)].
6
Evaluating Accuracy of Image Registration Methods
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The accuracy of the methods was compared using an intensity‐based criterion (correlation coefficient, CC)11 and volume‐based criterion (Dice's similarity coefficient, DSC).5 The correlation coefficient can be between −1 and +1. The value +1 represents a maximum correlation between the images.11 For the volume‐based criterion, the most common overlap metric is the DSC metric that computes the number of pixels that overlap between the two volumes. If the images have no overlap, the DSC is 0, and if the contours become identical, the DSC approaches a value of 1.5 Goldberg–Zimring et al.14 suggested that satisfactory volume matching should be 70% or greater for adaptive radiotherapy applications. An analysis of variance (ANOVA) using SPSS statistical software version 17 was used to assess the impact of each DIR method.
7
Factors Associated with TB Treatment Outcome
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Data were analysed with the use of the SPSS® statistical software version 17 (SPSS Inc., Chicago, USA). Chi square and Fisher’s exact tests were used to compare proportions, and Mann–Whitney U test was used to compare quantitative variables in both groups. Logistic regression analysis was used to determine the baseline factors associated with culture non-conversion at the end of the second month of intensive phase of antituberculosis therapy. Potential candidate predictors were first investigated in univariate analysis and significant variables (based on a threshold probability of 0.1) were all entered in the same multivariable logistic model to determine independent predictors for culture non-conversion in patients with persistent sputum smear positivity after two months of intensive therapy. A p-value <0.05 was used to characterize significant results.
8
Mortality Prediction in Indian Patients
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Assuming estimated mortality of around 10% over 2 years (as against 19.8% in MADIT II) in Indian population we calculated that the sample size of 144 patients would be required to detect this event rate with precision of ±5% with 95% confidence. Presuming drop rate of 10% in the study around 160 patients were planned to be included in the study.
Recruitment was stopped after 145 patients were enrolled. On interim analysis, as the target sample size of 144 was reached, only 1 patient was lost to follow-up and event rate was more than expected, further recruitment was stopped at 145 patients.
Microsoft excel was used to store the data from the patients and analysis were made with SPSS statistical software version 17 for Windows. Continuous variables were presented as mean ± standard deviation. Dichotomous variables were presented as count and percentage. Categorical variables were compared using Chi square and Fisher's exact test. Univariate and multivariate logistic regression models were used to determine the relationship between clinical characteristic and all-cause mortality. A p value < 0.05 was considered significant. Cumulative probabilities of survival were estimated by Kaplan–Meier methods and compare with Log-rank test.
Recruitment was stopped after 145 patients were enrolled. On interim analysis, as the target sample size of 144 was reached, only 1 patient was lost to follow-up and event rate was more than expected, further recruitment was stopped at 145 patients.
Microsoft excel was used to store the data from the patients and analysis were made with SPSS statistical software version 17 for Windows. Continuous variables were presented as mean ± standard deviation. Dichotomous variables were presented as count and percentage. Categorical variables were compared using Chi square and Fisher's exact test. Univariate and multivariate logistic regression models were used to determine the relationship between clinical characteristic and all-cause mortality. A p value < 0.05 was considered significant. Cumulative probabilities of survival were estimated by Kaplan–Meier methods and compare with Log-rank test.
9
Microbiological Evaluation of Orthodontic Brackets
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The results obtained with the aerobic and anaerobic culturing were analyzed descriptively by using the SPSS statistical software version 17 (SPSS Inc., Chicago, USA) to evaluate the level of contamination of the brackets by microorganisms and the level of significance was set at 0.05 (P < 0.05). A general linear model was used where repeated measures was used to fit the data ANCOVA tables were made to see whether there was an interaction effect between time and treatment and whether the separator material and day effects were significant. The following tests were performed like calculation of statistical parameters for parametric variables such as mean, standard deviation and 95% confidence interval of the mean aerobic and anaerobic CFU. Analysis of overall CFU was done by Tukey Honest Significant Difference (HSD) and Dunnett test. Tukeys test was based on the assumption that the observations being tested are independent, and there is equal within-group variance across the groups associated with each mean in the test. Dunnett test was used for comparing control to each of the other groups, but not comparing others to each other.
10
Kinetic Modeling of Pesticide Removal
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The removal of IPR and CHL from the liquid medium was fitted to the first-order kinetic model according to Equation (2):
where C0 is the initial concentration of the pesticides in the liquid medium, Ct is the concentration of the pesticides at time t, k is the degradation rate constant (h−1), and t is the reaction time (h). The degradation half-life (T1/2) is the time in which the pesticide concentrations in the liquid medium are reduced by 50% and was calculated using Equation (3).
Data were statistically analyzed using analysis of variance (ANOVA), and three replicates were compared using Tukey’s minimum significant differences test (p ≤ 0.05). Statistical analyses were performed using SPSS statistical software version 17.
where C0 is the initial concentration of the pesticides in the liquid medium, Ct is the concentration of the pesticides at time t, k is the degradation rate constant (h−1), and t is the reaction time (h). The degradation half-life (T1/2) is the time in which the pesticide concentrations in the liquid medium are reduced by 50% and was calculated using Equation (3).
Data were statistically analyzed using analysis of variance (ANOVA), and three replicates were compared using Tukey’s minimum significant differences test (p ≤ 0.05). Statistical analyses were performed using SPSS statistical software version 17.
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