Search

Positive and negative predictive values are useful to quantify the performance of medical tests, and both are often used simultaneously. Although there are several methods to test the equality of these predictive values between two medical tests, these approaches separately compare positive and negative predictive values. Therefore, we propose a testing procedure that combines the approximate likelihood ratio test defined by Tang et al. with the non-inferiority test for predictive values. The procedure can confirm that compared to an existing test, a new medical test is non-inferior in terms of both positive and negative predictive values, as well as superior regarding at least one of these values. It can make a comprehensive judgment of the performance of the new test based on both measures. A simulation study showed that the performance of the proposed testing procedure is appropriate, and the procedure is considered useful for evaluating the performance of predictive values of medical tests. [ABSTRACT FROM AUTHOR]

In some situations, square contingency tables with ordered categories are analyzed by considering collapsed tables where adjacent categories are combined. This study proposes measures to represent the degree of departure from symmetry using collapsed tables. The proposed measures are defined as the arithmetic mean of submeasures of each collapsed 3 × 3 table. Additionally, a theorem affirms that the value of the measure for symmetry is equal to the sum of the value of the proposed measures. Finally, examples are given. [ABSTRACT FROM AUTHOR]

The test treatment in confirmatory clinical trials is often assessed using multiple primary endpoints. We considered that trial efficacy is confirmed only when there is superiority of at least one endpoint and non-inferiority of the remaining endpoints. Some researchers proposed testing procedures for multiple primary endpoints that are continuous variables. However, there has not yet been discussion of the case in which a trial has multiple binary endpoints in the above framework. In this study, we consider a testing procedure for multiple primary endpoints that are binary, and evaluate the performance of the proposed method through simulations. [ABSTRACT FROM AUTHOR]

Predicting the prognosis of early-onset otitis media with effusion (OME) in children is difficult. To investigate the prognostic factors of OME in children undergoing tympanostomy at 1 year of age. We examined 66 children (123 ears) followed up to 6 years of age. OME prognosis was determined by a history of re-tympanostomy at the last examination. We retrospectively analysed the prognostic factors based on the duration of first ventilation tube (VT) placed, history of otorrhea, asthma, adenoidectomy, and mastoid air cell system (MACS) size at 1 year before tympanostomy and at 3 years. While 25 ears underwent re-tympanostomy (group 1), 98 did not (group 2). The mean duration of VT placed was 21 months and 25, and the mean MACS size at 3 years was 314 mm2 and 441, respectively, in the corresponding groups. MACS size at 3 years was significantly smaller in group 1 than in group 2. The combination of MACS size at 3 years and duration of VT placed showed the best value of area under the curve. The most probable prognostic factor was the combination of the MACS size at 3 years and duration of VT placed. [ABSTRACT FROM AUTHOR]

In clinical researches, various clinical scales with ordered categories are used to evaluate the efficacy and safety/toxicity of treatments. Such the clinical scales are sometimes summarized on the transition between the baseline and the study end point as a square contingency table. Also, clinical scales may be reclassified into three groups. However, the cutpoints can be varied depending on clinical researches or clinicians. Hence, this paper proposes a measure which is expressed by using same weights for collapsed tables and which can see the directionality for two kinds of asymmetries. Also, this paper shows an application of the proposed measure to clinical data, and that the proposed measure is a useful statistical method for analyzing ordered categorical data. [ABSTRACT FROM AUTHOR]

Positive and negative predictive values describe the clinical performance of the diagnostic test when it is applied to a cohort of individuals. Testing non-inferiority of predictive values may be adequate in some cases due to the simplicity of the examination and the invasiveness of the test, but no non-inferiority test for predictive values has been proposed yet. In this study, we propose a non-inferiority test that investigates the non-inferiority of predictive values in paired designs, and formulae for the calculation of sample size to execute the non-inferiority test of two predictive values. Simulation studies showed that the proposed non-inferiority test is useful for comparing two predictive values in clinical trials. [ABSTRACT FROM AUTHOR]

For square contingency tables with ordered categories, there may be some cases that one wants to analyze them by considering collapsed tables with some adjacent categories combined in the original table. This paper considers the symmetry model for collapsed square contingency tables and proposes a measure to represent the degree of departure from symmetry. The proposed measure is defined as the arithmetic mean of submeasures each of which represents the degree of departure from symmetry for each collapsed 3×3 table. Each submeasure also represents the mean of power-divergence or diversity index for each collapsed table. Examples are given. [ABSTRACT FROM AUTHOR]

For square contingency tables with ordered categories, there may be some cases that one wants to analyze them by considering collapsed tables with some adjacent categories combined in the original table. This paper proposes three kinds of new models which have the structure of point-symmetry (PS), quasi point-symmetry and marginal point-symmetry for collapsed square tables. This paper also gives a decomposition of the PS model for collapsed square tables. The father's and his daughter's occupational mobility data are analyzed using new models. [ABSTRACT FROM PUBLISHER]