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The two dropouts from CBT condition did not differ significantly from treatment completers on any tabulated variable.
To test this we ran a logistic regression model for each practice in turn and tabulated variable coefficients with any statistical significance for gender, age, co-morbidities, smoking status, SIMD code derived from patients' residential postcode and the use of the same SSRI for ≥2 years.
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Chi square (Χ 2 ) test was performed to test for statistical significance between proportions for the cross tabulated variables.
The results were expressed as percentages while Chi-square test was used to determine the statistical significance of key observations and differences seen in cross tabulated variables.
To characterize the sample, we assessed medians and interquartile ranges for continuous variables and tabulated categorical variables using SAS version 9.3 (SAS Inc., Cary, NC).
Data collected was tabulated by variable, using Statistical Package for the Social Sciences SPSSS for Windows, Version 10.0).
We tabulated clinical variables according to liver cirrhosis status and used Chi-squared, Fisher exact or Mann–Whitney U test for hypothesis testing as appropriate.
To better characterize the correlation between obesity and survival, multivariate analysis was performed using the tabulated demographic variables and comorbid conditions (Table 2).
We identified 19 tabulated continuous variables supposed to be normally distributed and for which a mean and a standard deviation were reported.
For each study, we tabulated six variables: number of cases, mean case SHBG levels, standard deviation of case SHBG levels, number of controls, mean control SHBG levels and standard deviation of control SHBG levels, using ngmol−1 as the units of SHBG.
Descriptive statistics including means and standard deviation (SD) were calculated for continuous variables, while proportions were calculated and tabulated for categorical variables.
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