Pasw version 18

Manufactured by IBM

Sourced in United States, Japan

PASW version 18.0 is a statistical software package developed by IBM. It is designed for data analysis, data management, and predictive modeling. The software provides a range of tools for researchers, analysts, and decision-makers to explore, analyze, and visualize data.

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Lab products found in correlation

Stata version 11, by StataCorp (3 mentions) R statistical software, by R Project for Statistical Computing (1 mentions) Sigmaplot software, by IBM (1 mentions) Sas version 9, by SAS Institute (1 mentions) Stata version 13, by StataCorp (1 mentions) Sigmaplot version 14, by Grafiti LLC (1 mentions) Prism 5, by GraphPad (1 mentions) Pasw statistic 18, by IBM (1 mentions) Ez test, by Shimadzu (1 mentions) Jsm 5310lv, by JEOL (1 mentions)

118 protocols using pasw version 18

Statistical Analysis of Oocyte Scores

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The experimental values for quantitative real-time PCR and The oocyte scores were statistically compared using one-sided Student's t-tests using PASW version 18 (IBM). The oocyte scores were statistically compared using the non-parametric Mann-Whitney U-test using PASW version 18 (IBM). Statistical significance was set at P < 0.05.

Otsuka-Kanazawa S., Ichii O, & Kon Y. (2015). Testicular oocytes in MRL/MpJ mice possess similar morphological, genetic, and functional characteristics to ovarian oocytes. Mechanisms of development, 137.

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Statistical Analyses in Biomedical Research

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Statistical analyses were performed using PASW version 18.0 (SPSS Inc., Chicago, IL, USA), Analyse-it Method Evaluation Edition software (version 2.26; Analyse-it Software Ltd., Leeds, UK), and R statistical software (version 3.6.3; R Foundation for Statistical Computing, Vienna, Austria). Categorical variables were compared using Pearson’s chi-square test or Fisher’s exact test. All tests were two-sided, and differences with P<0.05 were considered significant.

Jeong S., Lee N., Park M.J., Jeon K., Kim H.S., Kim H.S., Kim J.S, & Song W. (2022). Genotypic Distribution and Antimicrobial Susceptibilities of Carbapenemase-Producing Enterobacteriaceae Isolated From Rectal and Clinical Samples in Korean University Hospitals Between 2016 and 2019. Annals of Laboratory Medicine, 42(1), 36-46.

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Predicting Metabolically Unhealthy Obesity

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Data are expressed as means ± SD for continuous measures except for skewed continuous variables, which are presented as the median (interquartile range, 25–75%) or as proportions for categorical variables. Differences between groups were tested by the student t-test or Mann-Whitney U test for continuous variables and the χ²-test or Fischer’s exact test for categorical variables. Multiple logistic regression analysis with backward selection was used to determine independent associations between clinical and biochemical variables and future conversion to MUO as a binary variable. Odds ratios (ORs) with 95% confidence intervals (CI) were calculated for independent variables included in logistic models, with a 1-SD increment used for odds ratio calculations for continuous measurements. We assessed the presence of nonlinearity in the final model by inserting quadratic transformations of the three continuous variables that it contained into the model. The presence of interaction was tested in multivariate models by testing the significance of first order interaction terms. All statistical analyses were performed using PASW version 18.0 (SPSS, Chicago, IL, USA). A P-value of <0.05 was considered significant.

Hwang Y.C., Hayashi T., Fujimoto W., Kahn S., Leonetti D., McNeely M, & Boyko E. (2015). Visceral abdominal fat accumulation predicts the conversion of metabolically healthy obese subjects to an unhealthy phenotype. International journal of obesity (2005), 39(9), 1365-1370.

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Irisin Levels and Prediabetes/T2D

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All data are presented as means ± SDs or proportions, except for skewed variables, which are presented as medians (interquartile range, 25–75 %). One-way ANOVA, followed by Tukey’s posthoc test, and the Kruskal–Wallis test were used to compare the differences between the irisin tertiles. A linear-by-linear association χ²-test was used to perform trend analysis between the tertiles. The spearman correlation coefficients were calculated to compare the irisin and clinical and laboratory measurements. Multiple logistic regression analysis was used to calculate an odds ratio (OR) for the presence of pre-diabetes/T2D. The results of the analyses are presented as OR with a 95 % confidence interval (CI). All statistical analyses were performed using PASW version 18.0 (SPSS, Chicago, IL, USA). P values <0.05 were considered statistically significant.

Hwang Y.C., Jeon W.S., Park C.Y, & Youn B.S. (2016). The ratio of skeletal muscle mass to visceral fat area is a main determinant linking circulating irisin to metabolic phenotype. Cardiovascular Diabetology, 15, 9.

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Analyzing Citation Patterns in Trials

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We collected annual citation counts through December 2015 using Scopus. Citation data were updated as of 6 January 2016. We compared cumulative citation counts among positive, neutral, and negative trials graphically. Annual citation rates were calculated by dividing the total number of citations by the time elapsed from the earlier of the print or online publication dates and the end of 2015. Jadad quality scores were calculated by two study authors for each of the included trials; discrepancies were resolved by consensus [10 (link)]. We calculated the Pearson correlation coefficient to assess the relationship between trial size and annual citation rate. Data were collected and analyzed using Excel (Microsoft Corp., Redmond, WA, USA) and PASW version 18.0 (SPSS Inc, Chicago, IL, USA). The STROBE Statement checklist for observational studies is included as an additional file (see Additional file 1).

Misemer B.S., Platts-Mills T.F, & Jones C.W. (2016). Citation bias favoring positive clinical trials of thrombolytics for acute ischemic stroke: a cross-sectional analysis. Trials, 17, 473.

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Agonist Response Curve Analysis

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CRCs to agonists were fitted by non-linear regression using SigmaPlot software (version 11.0; SPSS, Inc.). The maximal responses (E_max) and the negative logarithm of the concentration at which agonists produce 50% of the maximum response were calculated. Statistical analysis was performed using PASW version 18.0 software (SPSS, Inc.). Data are expressed as the mean ± SD of ≥3 independent repeats. Differences within groups were compared using an unpaired Student's t-test or one-way analysis of variance (ANOVA) followed by LSD post hoc test. P<0.05 was considered to indicate a statistically significant difference.

Guo X., Deng Y., Zhan L., Shang J, & Liu H. (2021). O-GlcNAcylation contributes to intermittent hypoxia-associated vascular dysfunction via modulation of MAPKs but not CaMKII pathways. Molecular Medicine Reports, 24(5), 744.

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Polyp Detection Statistical Analysis

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The Student t-test was used to compare numerical variables between groups. The chi-square or Fisher exact test was used to compare categorical variables. The multivariate logistic regression model was used to identify independent variables associated with missed polyps or patients with missed polyps. ORs and 95% CIs and their associated P-values were calculated for per-polyp and per-patient associations. Values were considered statistically significant when P<0.05. All statistics were performed using predictive analytics software PASW version 18.0 (SPSS Inc., Chicago, IL, USA).

Kim N.H., Jung Y.S., Jeong W.S., Yang H.J., Park S.K., Choi K, & Park D.I. (2017). Miss rate of colorectal neoplastic polyps and risk factors for missed polyps in consecutive colonoscopies. Intestinal Research, 15(3), 411-418.

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ALDH1 Expression and Survival Outcomes

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Statistical analysis was performed by using PASW version 18.0 (SPSS Inc., Chicago, USA). Evaluation of pathologic differences and molecular subtypes according to ALDH1 expression were assessed by using the Pearson chi-square test. Kaplan-Meier estimates and curves were prepared for the survival outcomes. Multivariate analysis by using the Cox proportional hazards model was performed to assess the independent significance of pathologic factors and survival probabilities. Hazard ratios and their corresponding 95% confidence intervals were computed to provide quantitative information about the relevance of the statistical results. All p-values were obtained by performing two-sided testing, and p<0.05 was considered statistically significant.

Kim Y.S., Jung M.J., Ryu D.W, & Lee C.H. (2014). Clinicopathologic Characteristics of Breast Cancer Stem Cells Identified on the Basis of Aldehyde Dehydrogenase 1 Expression. Journal of Breast Cancer, 17(2), 121-128.

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Pregnancy Outcomes After Frozen Embryo Transfer

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All patients were retrospectively divided into the pregnant and the non-pregnant groups after FET. The variables under study were compared between the two groups by Wilcoxon rank sum test for independent samples using PASW version 18.0 (SPSS Inc., Chicago, IL, USA). The data were expressed as mean±standard deviation unless specified otherwise. The value of p<0.05 was considered statistically significant.

Hwang S.Y., Jeon E.H., Kim S.C, & Joo J.K. (2019). Clinical factors that affect the pregnancy rate in frozen-thawed embryo transfer in the freeze-all policy. Yeungnam University Journal of Medicine, 37(1), 47-53.

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Nonparametric Statistical Analysis of Research Data

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The data are presented as numbers (percentages) for categorical variables and medians (interquartile range [IQR]) for continuous variables. Because the data were nonparametric, Tukey's box and whisker plots were used to show centrality and dispersion. Statistical analyses were performed using the Kruskal-Wallis test or the Mann-Whitney U test with post-hoc paired comparisons using the Bonferroni method. All statistical analyses were performed using PASW version 18.0 (SPSS Inc., Chicago, IL, USA). p-values less than 0.05 were considered statistically significant.

Kim S.Y., Koh W.J., Park H.Y., Jeon K., Lee S.Y., Yim J.J, & Shin S.J. (2017). Down-Regulation of Serum High-Mobility Group Box 1 Protein in Patients with Pulmonary Tuberculosis and Nontuberculous Mycobacterial Lung Disease. Tuberculosis and Respiratory Diseases, 80(2), 153-158.

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