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Spss software version 26 64 bit for window

Manufactured by IBM

SPSS software version 26 (64-bit) for Windows is a statistical analysis software that provides a comprehensive set of tools for data management, analysis, and presentation. It allows users to explore, analyze, and visualize data, enabling them to uncover insights and patterns.

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Lab products found in correlation

2 protocols using spss software version 26 64 bit for window

1

Investigating Insulin Resistance Correlates

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All results are presented as mean ± standard deviation or if
skewed, as median (interquartile range, Q1-Q3) for the continuous variables, and
as a percentage for categorical variables. Differences between groups were
examined with Student’s t-test or Mann–Whitney’s test. The
relationships between indicators of IR and other factors were determined using
univariable linear regression and multivariable linear regression. Pearson’s r
and standardized B were calculated for the correlation between IR indices and
quantitative variables (such as developmental features of the fetus from
ultrasound findings, blood pressure, maternal weight, total cholesterol,
triglycerides, HDL-C, LDL-C, and hemoglobin) and dichotomous variables (family
history of diabetes, acanthosis nigricans, and lipid disorders). A
P-value < .05 was considered statistically significant.
Data were processed using SPSS software version 26 (64-bit) for Window (SPSS
Inc, Chicago, IL).
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2

Depression and Diabetes Patients

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All results are presented as mean (SD) or, if skewed, as median (interquartile range) for the continuous variables, and as a percentage for categorical variables. Differences between groups were examined with Student’s t-test or Mann–Whitney’s test. The chi-square test or fisher’s exact test of association is used to discover if there is a relationship between two categorical variables. The relationships between indicators of depression (or PHQ-9) and other factors were determined using univariable linear regression and multivariable linear regression. Pearson’s r and standardized B were calculated for the correlation between PHQ-9 indices and variables (such as age, gender, treatment therapy, and HbA1c control). The Kruskal–Wallis H-test was used to determine if there are statistically significant differences between the three groups of treatment options on the PHQ9-score. A p-value <0.05 was considered statistically significant. Data were processed using SPSS software version 26 (64-bit) for Window (SPSS Inc., Chicago, IL).
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