Statistical analysis was performed using SPSS (Statistical Package for Social Sciences) 12.0 for windows (SPSS, Chicago, IL, USA). Continuous and categorical variables were expressed as mean ± standard deviation (SD) (median [range]) and count (percentage), respectively. A chi square test was used to verify association or compare proportions. To compare continuous variables in the 2 groups, the Mann-Whitney U test was performed due to non-normal distributions. ROC curves were plotted to identify the best threshold for the potential predictors of rapid 131I turnover. AUC was used as an estimation of diagnostic accuracy. To identify associated factors of rapid 131I turnover, we performed multivariate logistic regression analysis with a variable entrance criterion of 0.05 or less. All P values presented were two-tailed, and values <0.05 were considered to be statistically significant.
12.0 for windows
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Sourced in United States
12.0 for windows is a software application developed by IBM that provides a suite of tools for data analysis and visualization. The core function of this product is to enable users to explore, manipulate, and present data in a variety of formats.
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Lab products found in correlation
4 protocols using 12.0 for windows
1
Predictors of Rapid Radioiodine Turnover
2
Age Estimation Methods Evaluation
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SPSS (Statistical Package for Social Sciences) 12.0 for Windows (SPSS, Inc., Chicago, IL) was used for all analysis
The differences between the chronological age and the estimated dental and skeletal ages were statistically tested using paired ‘t’ test (P value)
The correlation between chronological age, dental and skeletal age estimation methods was confirmed statistically by Pearson's correlation (r value). In all these tests, r value closest to 1 was considered to indicate the strongest relation between the comparisons
The inter-observer variability (r value) was tested using the Spearman's Correlation Coefficient. The relation was considered strongest between the pair whose value was closest to 1
The intra-observer variability was evaluated by recording the tooth calcification stages of 20 randomly selected patients who were evaluated individually by each of the three observers with an interval of 30 days between the two estimations. The reproducibility of the estimations was statistically tested using the Pearson's Chi-square test (P value)
Probability of predicting the ages accurately was evaluated for each method by multiple regression analysis.
3
Investigating Factors Predicting Teff
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Statistical analysis was performed using SPSS (Statistical Package for Social Sciences) 12.0 for windows (SPSS, Chicago, IL, USA). Normal distribution was tested with the Kolmogorov-Smirnov test. All data with normal distributions were expressed as mean ± standard deviation (SD) and data with non-normal distributions were expressed as median ± interquartile range (IQR). The relationships between Teff and continuous variables were analyzed by bivariate correlation (Pearson's or Spearman's correlation), while the relationships between gender, ATD or not, ADP and Teff were analyzed using 2-sided t test or one-way ANOVA analysis. Stepwise MLR analysis was performed to investigate factors that could be used to predict Teff, with a variable entrance criterion of 0.05 or less. All P values presented were two-tailed, and values < 0.05 were considered to be statistically significant.
4
Factors Predicting Abnormal Liver Function
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Statistical analysis was performed using SPSS (Statistical Package for Social Sciences) 12.0 for windows (SPSS, Chicago, IL). Continuous variables were expressed as mean ± standard deviation. A chi square test was used to test the gender variable. A Mann-Whitney U-test was used to determine differences between all the other continuous variables due to a non-normal distribution. Binary logistic regression analysis with a variable entrance criterion of 0.05 or less was used to determine the factors predicting abnormal LFTs. Receiver operating characteristic (ROC) curves were plotted to verify the accuracy for the prediction of abnormal LFTs. The area under curve (AUC) was used as an estimation of diagnostic accuracy. Missing values for anti-TPO (anti-Tg) and TRAb were assigned to the mean level. All P values presented were 2-tailed, and values <0.05 were considered to be statistically significant.
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