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Pasw statistics 19 for windows

Manufactured by IBM

PASW Statistics 19 for Windows is a statistical software package designed for data analysis. It provides a comprehensive set of tools for data manipulation, analysis, and visualization. The software is intended to assist users in exploring, analyzing, and interpreting data.

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Lab products found in correlation

2 protocols using pasw statistics 19 for windows

1

ABFM Therapy Outcomes: CR, CRD, and OS

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The endpoints of this single institution trial of ABFM therapy were CR, complete remission duration (CRD) and overall survival (OS). The CRD was measured from the date of CR until relapse. Differences in CR rates were analyzed by the chi squared or Fisher's exact tests. Unadjusted CRD and OS analyses were evaluated with Kaplan-Meier plots (12 ), and characteristics associated with differences in CRD and OS were assessed by log-rank testing (13 (link)). Cox proportional hazard regression (14 ) was used to evaluate factors predicting CRD and OS. Factors with a p-value ≤ .10 by univariate analysis were entered into the multivariate analysis. We found that MRD at Days 29 and 84 or greater were collinear and could not be included in the same model. Therefore, we constructed separate models to assess the effect of MRD at Days 29 and 84, separately. A p-value of <.05 was considered statistically significant. All statistical analyses were performed with IBM PASW Statistics 19 for Windows (SPSS Inc., Chicago, Illinois).
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2

Comparative Analysis of ABFM and Hyper-CVAD Trials

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The endpoints of both ABFM and hyper-CVAD trials were CR, CR duration (CRD), and overall survival (OS). The CRD was measured from the date of CR until relapse. Differences in CR rates were analyzed by the chi squared or Fisher’s exact tests. The CRD and OS times were assessed by the Kaplan–Meier method [16 ]. Characteristics associated with differences in CRD and OS were assessed by log-rank testing [17 (link)]. Cox proportional hazard regression was used to evaluate factors predicting CRD and OS [18 ]. Factors with a P value ≤0.10 by univariate analysis were entered into the multivariate analysis. A P value of <0.05 was considered statistically significant. Statistical analyses were performed with IBM PASW Statistics 19 for Windows (SPSS, Chicago, IL).
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