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Statistical package for the social science spss version 22

Manufactured by IBM
Sourced in United States

SPSS version 22 is a software package that provides statistical analysis and data management functionality. It is designed to work with structured data and offers a wide range of statistical techniques, including regression analysis, correlation, and hypothesis testing. The software is commonly used in the social sciences, market research, and other data-driven fields.

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Lab products found in correlation

2 protocols using statistical package for the social science spss version 22

1

Internet Use and Quality of Life in Thyroid Cancer Patients

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Statistical analyses were performed using the IBM Statistical Package for the Social Science (SPSS) version 22 (IBM Corp., Armonk, NY USA). Descriptive statistics were used to summarize the socio-demographic and clinical characteristics and the data on Internet use and QOL.
We defined health-related Internet users as “TL patients who had ever searched for information about their health on the Internet” and cancer-related Internet users as “TL patients who had ever searched for information about cancer on the Internet”. Chi-squared tests, independent samples t tests, and Mann-Whitney tests were used to compare socio-demographic and clinical characteristics among TL patients. Statistical significance was assumed when p value was < .05 (two-tailed).
Stepwise logistic regression analyses were performed to assess the relative importance of the variables (Nagelkerke R2) that were univariately associated (p value to enter < .05) with Internet use, health-related Internet use, or cancer-related Internet use. In the first block of the regression analysis, the demographic characteristics were entered (age, gender, education level, and employment status), followed by the clinical characteristics and QOL in the second block (time since TL and QOL).
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2

Stroke Rehabilitation Fall Risk Predictors

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Patients were grouped by the type of stroke (hemorrhagic versus non-hemorrhagic), and by the laterality of stroke (left, right, or bilateral). All categorical variables, such as gender, age group, falling status and type of stroke, were presented as numbers and percentages. Continuous variables, such as age and hospital stay, were expressed as mean±standard deviation. The Pearson chi-square test or Fisher exact test was used to analyze the data depending on whether the cell expected frequency was smaller than 5 in cross-tabulation, and to determine any significant relationship between the categorical variables. Binary logistic regression was used to evaluate predictors of falls during rehabilitation. A p-value<0.05 was considered statistically significant. All data were entered and analyzed using the Statistical Package for the Social Science (SPSS) Version 22 (IBM Corp., Armonk, NY, USA).
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