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T Tango

Publications and source records attributed to T Tango.

65 records · Page 4Linked to original sources
PubMed1980

On the methods calculating mean survival time in 51Cr-platelet survival study.

The International Committee for Standardization in Hematology recommended three methods for calculating objectively the mean platelet survival time, ie, weighted mean of linear estimate and logarithmic estimate, truncated exponential model, and gamma model. For determining which method is better, data of the survival study were fitted to each of three methods, as well as the Paulus polynomial and exponential polynomial models, and the mean survival time and the mean square error were compared. Mean survival obtained by each method was always longest in healthy controls and shortest in ITP. In 3rd degree of polynomial estimate and 2nd and 3rd degrees of logarithmic estimate, several cases showed practically outlying mean survival time of more than 12 days. In healthy controls, highest mean square error was observed in 1st degree logarithmic estimate, and in cases with short mean survival time the highest one was obtained in 1st degree polynomial estimate. Mean square error in ITP pre- and postsplenectomy and in aplastic anemia was smallest in the gamma model. Among nine methods recommended by the International Committee for Standardization in Hematology and by Dr. Paulus, the gamma model so far provides the best method for calculating the mean survival time of 51Cr-platelets.

Blood Platelets↗
PubMedDate not supplied

Estimation of normal ranges of clinical laboratory data.

This paper proposes a new procedure for estimating normal ranges of clinical laboratory tests, which can be applied to data with possibly more than one outlier from healthy subjects. The proposed procedure determines the optimal model among a class of models in which it is assumed that an observed distribution of 'normal values' can be transformed to the Gaussian form by one of several specified transformations, and if there exist outliers among the data, then each of the transformed outliers also follows a Gaussian distribution with different mean from, but the same variance as, the transformed distribution of normal values. The optimal model is defined as the best combination of the transformation to normality and the number of outliers identified, and is selected by the Akaike information criterion (AIC). Our procedure is illustrated with data from 200 healthy male subjects on 25 laboratory tests.

Adult↗
PubMedDate not supplied

A class of tests for detecting 'general' and 'focused' clustering of rare diseases.

This paper proposes a class of tests applicable to the detection of two types of disease clustering 'focused' and 'general' clustering. The former assesses the clustering of observed cases around the fixed point and the latter does not have any prior information on the centre of clustering. The proposed test for 'general' clustering is a generalization of the index for temporal clustering proposed by Tango in that it adjusts for differences in population densities and also in population distributions among categories of the counfounders such as age and sex. Simulation study shows that the proposed 'general' test outperformed the average distance method of Whittemore et al. in most of the cluster models considered.

Cluster Analysis↗
PubMedDate not supplied

An interpretation of normal ranges based on a new concept "individual difference quotient" of clinical laboratory data.

This article presents a new interpretation of so-called clinical normal ranges which have recently been shown to have a wide range in comparison to the narrow individual physiological fluctuations, based on a newly introduced concept "individual difference quotient" of clinical laboratory data. This quotient is defined as the ratio of inter- or intra-individual dispersion within the framework of a random-effects one-way analysis of variance model and can be used as a useful criterion to compare the degrees of individual differences of clinical laboratory tests with different measurement units. Further, as a function of this quotient the probability that a test result for a specific person falls within the normal range of this person can be derived. The derived probability can be expected to play a significant role in assessing an individual's state of health.

Clinical Laboratory Techniques↗