All data are presented as percentages or as means with standard deviation. Numerical data were tested for statistical significance using an independent two-sample test or ANOVA as appropriate. The Pearson chi-square test or Fisher's exact test were used to test for statistical significance when considering nominal variables. Survival rates were calculated, and plots constructed, using the Kaplan-Meier method, and groups were compared using a log-rank test. All statistical analyses were performed using the SPSS computer software package (Version 10.0, Chicago, IL, USA). A p-value <0.05 was considered statistically significant.
Spss computer software package
Manufactured by IBM
Sourced in United States
SPSS is a computer software package used for statistical analysis. It is designed to perform a wide range of data analysis and manipulation tasks, including descriptive statistics, regression analysis, and hypothesis testing. The software is widely used in various fields such as social sciences, business, and healthcare.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using spss computer software package
1
Comprehensive Statistical Analysis of Experimental Data
2
Semen Bacterial Enumeration Protocol
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Data were expressed as means (±standard error of the mean) CFU/ml of semen and analyzed by applying general linear model for factorial experiments using SPSS computer software package (Version 16.0.0.247©2007). Duncan’s multiple range tests was done to make specific treatment comparisons for values that were found significant by ANOVA.
3
Survival Outcomes in Chronic Disease
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All data are presented as percentages of patients or means with SDs. Pearson Chi-square test and Fisher exact test were used for nominal variables. Survival rates were calculated and plotted with the Kaplan-Meier method and compared between groups with a log-rank test. All statistical analyses were performed using the SPSS computer software package (version 10.0; SPSS, Chicago, IL). A P value of less than .05 was considered to be statistically significant.
4
Residential Radon Exposure and Lung Cancer Risk
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Data were analyzed using a multivariate Cox regression model in which the dependent variable was development of lung cancer. Residential radon concentration was used as the independent variable in two categories, with the cut-off point set at 50Bq/m 3 . The adjustment variables were sex, age and tobacco use. Tobacco use was calculated on the basis of two surveys (initial and final) and measured in pack-years (packs smoked per year). The time-scale used was duration (years) of follow-up for each participant. The results were expressed as hazard ratios (HRs) with a 95% confidence interval (95%CI). Any subject who developed any non-pulmonary cancer during follow-up was counted as lost to follow-up. Four other models were fitted, with each restricted as follows: men only (due to the low number of observed cases in women); only individuals who had been living in the same dwelling for more than 25 years; only persons who were over the age of 50 years at the date of their inclusion in the cohort; and lastly, according to participants' study of origin (Galician radon map and controls from the case-control study). Crude and adjusted models were fitted for each of these categories. All analyses were performed using version 21 of the SPSS computer software package (SPSS Inc., Chicago, USA).
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