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Spss statistical software version 24

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SPSS Statistical Software Version 24 is a comprehensive set of data analysis tools designed to address a wide range of statistical requirements. It provides advanced analytical capabilities to help users gain meaningful insights from their data.

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Lab products found in correlation

Prism 8, by GraphPad (3 mentions) Matlab version r2018b, by MathWorks (1 mentions) R version 4, by R Project for Statistical Computing (1 mentions) Stata 14, by StataCorp (1 mentions) Prism v7, by GraphPad (1 mentions) Spss statistics version 24, by IBM (1 mentions) Stata statistical software, by StataCorp (1 mentions) R statistical software version 3, by R Project for Statistical Computing (1 mentions) Excel 2016, by IBM (1 mentions) R version 3, by R Project for Statistical Computing (1 mentions)

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185 protocols using spss statistical software version 24

1

Predicting CD8+ TIL Levels Using Imaging Features

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Statistical tests were performed using IBM SPSS statistical software version 24 (IBM Corp., Armonk, New York, USA), R language version 4.0.2 (R Core Team, 2020), or Medcalc Statistical Software Version 22 (Medcalc Software Ltd., Ostend, Belgium). Continuous variables were compared using the independent samples two-sided t-test or the Mann-Whitney U test, depending on the data distribution. Categorical variables were expressed as numbers (%) and compared using the chi-squared test or Fisher’s exact test. The p-values for multiple comparisons were adjusted using Bonferroni’s correction. Univariate and multivariate logistic regression analyses were used to identify the optimal features for predicting CD8+-TIL levels. The predictive models were constructed using stepwise multivariate logistic regression analysis. The predictive performance of CD8+-TIL levels based on US and MRI features was determined using receiver operating characteristic (ROC) analysis, respectively. The area under the ROC curve (AUC) was compared using the DeLong test. All comparisons were considered statistically significant at a p-value of < 0.05.
Fan Y., Li X., Zhong P., Guo H., Han D., Tian W, & Fan J. (2024). Radiological Features for Predicting the Status of CD8-Positive Lymphocytes in HER2 Positive Breast Cancer. Balkan Medical Journal, 41(3), 213-221.
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2

Assessing Clinician-Caregiver Wellness across Specialties

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Data were analyzed using SPSS statistical software version 24 (IBM Corp). Statistical significance was set at P < .05, and all tests were 2-tailed. The total CCWAS score was computed for each participant. Internal consistency was evaluated using Cronbach α, and the Kaiser-Meyer-Olkin and Bartlett tests were used to examine sampling adequacy and suitability for factor analysis. A principal components analysis was conducted using promax rotation to examine the factor structure and dimensionality of the scale. The Kaiser criterion (eigenvalues, >1.0) was used to examine the number of factors, and the rotated component matrix was used to ensure all items loaded appropriately on a factor.
Nonparametric statistical tests were used to compare CCWAS scores between genders, age groups, faculty status, and parental status. Stepwise linear regression was performed to examine the association of participant characteristics with CCWAS scores. Variables included gender, years in practice, faculty status, and parental status. To examine generational differences, participants were categorized into senior and junior groups, as described earlier.
Ruzycki S.M., Freeman G., Bharwani A, & Brown A. (2019). Association of Physician Characteristics With Perceptions and Experiences of Gender Equity in an Academic Internal Medicine Department. JAMA Network Open, 2(11), e1915165.
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3

Statistical Analysis of Experimental Data

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The data are expressed as the means ± SEM. Statistical analysis of the results was performed by using Mann-Whitney U test. The minimum sample size was 4. In all cases, differences were considered significant at p < 0.05. All analyses were performed using the SPSS statistical software version 24 (IBM Corp., NY, USA).
Tey S.L., Li C.Y., Lin L.W., Chang L.C., Chen Y.L., Chang F.R., Yang S.N, & Tsai C.C. (2021). Arecae pericarpium extract induces porcine lower-esophageal-sphincter contraction via muscarinic receptors. BMC Complementary Medicine and Therapies, 21, 275.
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4

Copeptin Baseline and Intervention Effects

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Significance of differences between baseline and postintervention measurements was tested by using a paired t test or Wilcoxon paired-rank test, depending on distribution. Furthermore, participants were divided into subgroups according to baseline copeptin concentration (top tertile of copeptin vs tertiles 1 and 2). Significance of differences between these two subgroups was tested by using an independent sample t test or Mann-Whitney U test depending on normality; a Fisher exact test was used for dichotomous variable. Finally, significant difference in change of fasting glucose was tested in subgroups defined by baseline copeptin using a one sample t test. SPSS statistical software version 24 (IBM Inc., Chicago, IL) was used for all analyses. A two-sided P value < 0.05 was considered to indicate a statistically significant difference.
Enhörning S., Brunkwall L., Tasevska I., Ericson U., Persson Tholin J., Persson M., Lemetais G., Vanhaecke T., Dolci A., Perrier E.T, & Melander O. (2018). Water Supplementation Reduces Copeptin and Plasma Glucose in Adults With High Copeptin: The H2O Metabolism Pilot Study. The Journal of Clinical Endocrinology and Metabolism, 104(6), 1917-1925.
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5

Residential Status and Patient Characteristics

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We report the distribution of characteristics overall and stratified by residential status (ie, long-term health care facility vs other residence). To compare characteristics according to residential status, we used descriptive statistics, the χ2 and Fisher exact tests for categorical variables, and t and Wilcoxon tests for continuous variables. All analyses were conducted on SPSS statistical software version 24 (IBM Corp). A P ≤ .05 was considered statistically significant, and all tests were 2-tailed.
Yang B.Y., Barnard L.M., Emert J.M., Drucker C., Schwarcz L., Counts C.R., Murphy D.L., Guan S., Kume K., Rodriquez K., Jacinto T., May S., Sayre M.R, & Rea T. (2020). Clinical Characteristics of Patients With Coronavirus Disease 2019 (COVID-19) Receiving Emergency Medical Services in King County, Washington. JAMA Network Open, 3(7), e2014549.
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6

Validation of Consumer Physical Activity Monitors

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Analyses were conducted jointly using IBM SPSS statistical software version 24 (IBM Corporation, Armonk, NY) and R statistical software. Data are presented as mean (SD). Participants were excluded from final analyses for: 1) not completing 2 visits (n = 7) or 2) declining to wear the K4b2 on one or both visits (n = 4). Of the remaining 89 participants, there were additional synchronization errors for the consumer PAMs resulting in exclusion of participants that wore the Apple Watch 2 (n = 23), Fitbit Charge 2 (n = 10), Samsung Gearfit2 (n = 17), Misfit Shine 2 – Hip (n = 68), Misfit Shine 2 – Shoe (n = 70), and Mymo (n = 21). Thus, the final analytic sample for each device was: Apple Watch 2 (n = 64), Fitbit Charge 2 (n = 38), Samsung Gearfit2 (n = 23), Misfit Shine 2 – Hip (n = 21), Misfit Shine 2 – Shoe (n = 19), and Mymo (n = 65). Due to the unequal sample sizes, each device was examined separately.
Three analyses were done for each consumer PAM: 1) paired samples t-test comparing the estimated EE of each consumer PAM and measured EE from the K4b2, 2) a 2×2 ANOVA (EE estimate × age group [dichotomized by 6–12 and 13–18 years old, and 3) a 2×2 ANOVA (EE estimate × sex). Performance was further assessed using Bland-Altman plots and mean absolute percent error (MAPE). Significance was set at alpha = 0.05.
LaMunion S.R., Blythe A.L., Hibbing P.R., Kaplan A.S., Clendenin B.J, & Crouter S.E. (2019). Use of Consumer Monitors for Estimating Energy Expenditure in Youth. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme, 45(2), 161-168.
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7

Statistical Analysis of Research Data

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Descriptive statistics are provided as counts and percentages for categorical variables, and mean and standard deviation (SD) for continuous variables. All analyses were performed using SPSS statistical software version 24 (IBM Corp, Armonk, NY, USA) and R software version 4.0.2.
Wang Y.H., Wang T.B., Zhang Z.X., Liu H.X., Xu T.M., Wang C, & Jiang B.G. (2021). Development and internal validation of China mortality prediction model in trauma based on ICD-10-CM lexicon: CMPMIT-ICD10. Chinese Medical Journal, 134(5), 532-538.
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8

Kaplan-Meier Analysis of PFS and OS

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PFS was defined from date of diagnosis to disease progression, relapse, or death from any cause. OS was defined from date of diagnosis to death. PFS and OS were estimated using the Kaplan-Meier method.21 (link) Median follow-up time and 95% CIs were estimated using the reverse Kaplan-Meier method.22 (link) We do not report any data that used t tests in this analysis, and no comparisons were performed, so no prespecified level of significance was set. Statistical analyses were performed using Prism version 8.0 (GraphPad) and SPSS statistical software version 24 (IBM Corp).
Pinnix C.C., Gunther J.R., Fang P., Bankston M.E., Milgrom S.A., Boyce D., Lee H.J., Nair R., Steiner R., Strati P., Ahmed S., Iyer S.P., Westin J., Parmar S., Rodriguez M.A., Nastoupil L., Neelapu S., Flowers C, & Dabaja B.S. (2020). Assessment of Radiation Doses Delivered to Organs at Risk Among Patients With Early-Stage Favorable Hodgkin Lymphoma Treated With Contemporary Radiation Therapy. JAMA Network Open, 3(9), e2013935.
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9

Analgesic Regimen Comparison Study

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A priori power analysis was performed to detect a difference with an effect size of 0.40 using an α of 0.05 and a β of 0.80. The analysis determined that a minimum sample size of 64 patients (32 in each group) was needed. Statistical analysis was performed using SPSS statistical software version 24 (IBM, Armonk, NY). Differences between the 2 analgesic regimens were analyzed using independent-samples t tests for continuous variables and chi-squared tests for categorical variables. Linear regression analyses were done to assess for correlations among variables. Findings were considered significant if P ≤ .05.
Thompson K.A., Klein D., Alaia M.J., Strauss E.J., Jazrawi L.M, & Campbell K.A. (2020). Opioid Use Is Reduced in Patients Treated with NSAIDs After Arthroscopic Bankart Repair: A Randomized Controlled Study. Arthroscopy, Sports Medicine, and Rehabilitation, 3(1), e15-e22.
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10

Statistical Analysis of Categorical and Continuous Data

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Chi-squared analysis or Fisher exact tests were used to compare
categorical data, and Mann-Whitney U test was used to compare
continuous variables. All statistical analyses were performed using the SPSS
Statistical software, version 24 (IBM, Armonk, NY) and statistical significance
was defined as a p-value of <0.05.
Favazza L.A., Parseghian C.M., Kaya C., Nikiforova M.N., Roy S., Wald A.I., Landau M.S., Proksell S.S., Dueker J.M., Johnston E.R., Brand R.E., Bahary N., Gorantla V.C., Rhee J.C., Pingpank J.F., Choudry H.A., Lee K., Paniccia A., Ongchin M.C., Zureikat A.H., Bartlett D.L, & Singhi A.D. (2020). KRAS Amplification in Metastatic Colon Cancer is Associated with a History of Inflammatory Bowel Disease and May Confer Resistance to anti-EGFR Therapy. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 33(9), 1832-1843.
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