Spss 20 for windows

Manufactured by IBM

Sourced in United States, Japan, United Kingdom

SPSS 20 for Windows is a statistical software package developed by IBM. It provides tools for data analysis, data management, and data visualization. The software is designed to handle a wide range of data types and can be used for a variety of statistical analyses, including regression, correlation, and hypothesis testing.

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Lab products found in correlation

Prism 5, by GraphPad (2 mentions) Stata 12, by StataCorp (1 mentions) Prism 6, by GraphPad (1 mentions) Guidezilla, by Boston Scientific (1 mentions) Spss 20 statistical package, by IBM (1 mentions) Amos 20, by IBM (1 mentions) Prism v7, by GraphPad (1 mentions) Micromass quattro micro mass spectrometer, by Waters Corporation (1 mentions) Dna degradase plus, by Zymo Research (1 mentions) Statview, by Abacus (1 mentions) Originpro 8, by OriginLab (1 mentions) Prism 7, by GraphPad (1 mentions) Stata se version 11, by StataCorp (1 mentions) Spss statistics for window, by IBM (1 mentions)

Close spelling variants of this product

SPSS 20.0 (6611 citations) SPSS version 20.0 for Windows (272 citations) SPSS v.20 for Windows (73 citations) SPSS V.20.0 for Windows (70 citations) SPSS Windows (23 citations) SPSS statistical software version 20.0 for Windows (14 citations) SPSSTM (8 citations) SPSS 20.0 Statistical Package Program for Windows (7 citations) SPSS program for Windows version 20.0 (6 citations) SPSS for Window (5 citations)

309 protocols using spss 20 for windows

Mortality Predictors in Clinical Study

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Variables were divided into categorical and continuous groups. Categorical variables were expressed as numbers and percentages. The χ² test was used to analyze categorical variables. Continuous variables were shown as mean and standard deviation. The Kolmogorov-Smirnov test was used to determine whether continuous variables had a normal distribution or not. Normally distributed variables were analyzed by the independent samples t-test. Non-normally distributed variables were analyzed by the Mann-Whitney U test. Independent predictors for mortality were determined by the binomial logistic regression analysis using p < 0.05 as the criterion. The program SPSS for Windows 20.0 (SPSS, Armonk, New York, USA) was used for statistical analysis. A p < 0.05 was considered to be statistically significant.

Dönmez Y., Urgun Ö.D, & Kurt İ.H. (2019). T wave positivity in lead aVR is associated with mortality after transcatheter aortic valve implantation. Archives of Medical Sciences. Atherosclerotic Diseases, 4, e55-e62.

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Father-Child Attachment Relationships Study

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Statistical analysis was performed using SPSS for Windows 20.0. In light of study objectives, descriptive statistics included frequency analysis and calculations of ratio, mean, and standard deviation (SD) values. Inferential statistics included independent-samples t-tests, paired-samples t-tests, and chi-square tests, with values of p < .05 considered significant. Variables identified in univariate analysis as having significant differences were classified as moderators, which were then introduced into the ANCOVA model in order to explore the effect of the intervention on the father-child attachment relationships after controlling for confounding variables.

Chen E.M., Gau M.L., Liu C.Y, & Lee T.Y. (2017). Effects of Father-Neonate Skin-to-Skin Contact on Attachment: A Randomized Controlled Trial. Nursing Research and Practice, 2017, 8612024.

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Rehabilitation Effectiveness Analysis

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The study data statistical analysis was performed using the SPSS for Windows 20.0 program. Quantitative indicators of the rehabilitation and control groups were compared using Student’s (t) test, the mean value standard errors (±SE) were presented; qualitative—using Chi-square (x2) test. The treatment effect after 1 and 6 months was assessed using analysis of covariance (ANCOVA). In the ANCOVA, the data after 1 and 6 months were used as dependent variables, the variables before the operation—as a covariate, and the patients group—as a factor. Verification of statistical hypotheses selected statistical confidence level of p < 0.05 (95% statistical confidence).

Jakubsevičienė E., Vasiliauskas D., Velička L., Kubilius R., Milinavičienė E, & Venclovienė J. (2014). Effectiveness of a New Exercise Program after Lower Limb Arterial Blood Flow Surgery in Patients with Peripheral Arterial Disease: A Randomized Clinical Trial. International Journal of Environmental Research and Public Health, 11(8), 7961-7976.

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Triplicate Experimental Analysis

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All experiments were conducted in triplicate, and the results are expressed as mean ± SD. One-way analysis of variance was performed in SPSS for Windows 20.0 (SPSS Inc., Chicago, IL, USA).

Meng J., Xu J., Huang C, & Chen J. (2020). Rcs Phosphorelay Responses to Truncated Lipopolysaccharide-Induced Cell Envelope Stress in Yersinia enterocolitica. Molecules, 25(23), 5718.

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Molecular Mechanisms of Cell Signaling

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Data are presented as mean ± standard deviation (s.d.). Statistical analysis was performed by one-way ANOVA analysis and t-test using SPSS for Windows 20.0 (SPSS, Inc.). P < 0.05 was considered to indicate a statistically significant result.

Jing L, & Chengji W. (2019). GC/MS-based metabolomics strategy to analyze the effect of exercise intervention in diabetic rats. Endocrine Connections, 8(6), 654-660.

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Detailed Statistical Analysis Methods

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All data are expressed as mean ± SEM. For comparison of WKY and Control groups, independent sample’s t-test (2-tailed) was applied. Control and Treatment groups were analyzed using one-way ANOVA (SPSS for Windows 20.0). For post hoc comparison Dunnett’s test (2-tailed) was chosen. In cases of inhomogeneous group variances Welch correction was applied followed by Dunnett T3 post hoc test. On GCL cell number data Kruskal–Wallis test was conducted, due to extreme non-normal distribution of the FGY400 group. Values of p < 0.05 were considered statistically significant. All individual data are tabulated in the Appendix.

Deres L., Eros K., Horvath O., Bencze N., Cseko C., Farkas S., Habon T., Toth K, & Halmosi R. (2019). The Effects of Bradykinin B1 Receptor Antagonism on the Myocardial and Vascular Consequences of Hypertension in SHR Rats. Frontiers in Physiology, 10, 624.

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Methamphetamine Abstinence and Attendance

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For all baseline comparisons of continuous variables across groups, ANOVAs were performed. For all baseline comparisons of categorical variables across groups, chi-square tests were performed. We utilized generalized estimation equations (GEE) to analyze attendance and methamphetamine abstinence during treatment (Twisk 2003 ). We also conducted GEE analyses to analyze repeated assessments of methamphetamine abstinence and attendance during follow-up.
Missing data were handled by imputing a positive methamphetamine UA for those who dropped out during the 16-week treatment phase. This was done as our variable of interest was attendance and provision of a methamphetamine-negative urine test. Patients were allowed to miss one session of treatment per week for approved reasons (e.g., health or child-care issues), and thus these approved missed visits were not considered missing data and were therefore not imputed. This is a method that has been used consistently in the analysis of trials similar to the one reported here (Peirce et al. 2006 (link); Petry et al. 2005 (link); Roll et al. 2006 (link)). Analyses were performed using Stata 12.1 (StataCorp, College Station, TX) and SPSS for Windows 20.0.

Chudzynski J., Roll J.M., McPherson S., Cameron J.M, & Howell D.N. (2015). Reinforcement Schedule Effects on Long-Term Behavior Change. The Psychological record, 65(2), 347-353.

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Psychological Factors in Endoscopic Diagnosis

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Data were entered into SPSS for Windows 20.0 (SPSS Inc., Chicago, IL, USA). Descriptive analyses were run for frequencies of socio-demographic, clinical characteristics and lifestyle-related behaviors of the sample. Multivariate analyses of variance using the General Linear Model were performed to test the associations between DCPR-R classification and scores obtained from the dimensional psychological measures (SQ) and the association between DCPR-R diagnoses and psychological well-being (PWB-I) scores. To evaluate the associations between DCPR classification, lifestyle and endoscopic diagnoses, χ²-test applied to contingency tables was used, as appropriate. Significance level was set to 0.05, two-tailed.

Gostoli S., Montecchiarini M., Urgese A., Ferrara F., Polifemo A.M., Ceroni L., Gasparri A., Rafanelli C, & Cennamo V. (2021). The clinical utility of a comprehensive psychosomatic assessment in the program for colorectal cancer prevention: a cross-sectional study. Scientific Reports, 11, 15575.

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Statistical Analysis of Psychological Measures

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All data from the paper‐based survey forms were manually entered into the statistical software package SPSS for Windows 20.0. Descriptive statistics for the sample, CBI and DASS subscales were generated. As DASS scores were skewed, non‐parametric Spearman's rho was used to identify correlations between CBI and DASS subscales. DASS subscale scores were used as continuous variables and also collapsed into two groups (normal/mild versus moderate to extremely severe) using cut‐points provided in the DASS User's Manual (Crawford & Henry, 2003 (link); Lovibond & Lovibond, 1995 ).

Vaičienė V., Blaževičienė A., Macijauskiene J, & Sidebotham M. (2021). The prevalence of burnout, depression, anxiety and stress in the Lithuanian midwifery workforce and correlation with sociodemographic factors. Nursing Open, 9(4), 2209-2216.

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Statistical Analysis of Research Data

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Data have been stored in a dedicated database and analyzed with SPSS for Windows 20.0 (SPSS Inc, Chicago, IL). A p value <0.05 was considered statistically significant. Categorical variables are reported as frequencies and percentages; continuous variables are reported as mean ± standard deviation (SD) or median (range), as needed. Comparisons between the groups were performed using chi-square for categorical data, and Student t test and Kruskal-Wallis test for continuous data.

Lazzeri C., Bonizzoli M., Batacchi S., Cianchi G., Franci N., Socci F, & Peris A. (2021). Persistent Right Ventricle Dilatation in SARS-CoV-2–Related Acute Respiratory Distress Syndrome on Extracorporeal Membrane Oxygenation Support. Journal of Cardiothoracic and Vascular Anesthesia, 36(7), 1956-1961.

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