Statistical analyses were conducted with PQStat version 1.8.0.392 and IBM SPSS Statistic version 21. As the entire accessible student population was tested, no prior sample calculation was performed. However, a post-hoc power calculation was performed using a Chi-square test (RxC) for a population of 88 participants. The calculated post-hoc power for each test is shown in Table 3.
There were no undetermined results or missing values. The descriptive statistics for the quantitative variables are given as the mean ± SD. The statistical analysis of different flavour dysfunctions and questionnaire questions between the population subgroups was performed using the chi-square test. If there were fewer than five people in any field of the analysed subgroup, a Yates correction was applied. The level of statistical significance was set at P ≤ .05 with a 95% confidence interval.
The diagnostic test confidence interval (sensitivity, specificity and predictive values of the particular taste) was calculated based on the Clopper-Pearson method for a single proportion. The clinical accuracies of the tests were determined using receiver operator characteristic (ROC) plots. The ROC area under the curve (AUC) was calculated as the fraction 'correctly identified to be positive' and the fraction 'falsely identified to be positive' determined according to the questionnaire answers and flavour tests.
There were no undetermined results or missing values. The descriptive statistics for the quantitative variables are given as the mean ± SD. The statistical analysis of different flavour dysfunctions and questionnaire questions between the population subgroups was performed using the chi-square test. If there were fewer than five people in any field of the analysed subgroup, a Yates correction was applied. The level of statistical significance was set at P ≤ .05 with a 95% confidence interval.
The diagnostic test confidence interval (sensitivity, specificity and predictive values of the particular taste) was calculated based on the Clopper-Pearson method for a single proportion. The clinical accuracies of the tests were determined using receiver operator characteristic (ROC) plots. The ROC area under the curve (AUC) was calculated as the fraction 'correctly identified to be positive' and the fraction 'falsely identified to be positive' determined according to the questionnaire answers and flavour tests.