PubMed · 649029
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H Flügel. 1978-06-01. [Cholelitholysis].. https://pubmed.ncbi.nlm.nih.gov/649029/
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Cholesterol stones in the gallbladder can be dissolved in 60 to 90% by oral administration of chenodeoxycholic acid, ursodeoxycholic acid or the combination of both. The effect depend on the number and size of stones. Treatment is without any side effects and lethality. A great number and large stones can be dissolved by direct instillation of methyl-tert-butyl-ether (MTBE) into the gallbladder using the percutaneous transhepatic method. The success rate amounts to 90%, the average therapy duration is 9 hours. Solvents for chemolitholysis of pigmented stones are being tested.
The most common instance of multivariate observations is the case of repeated measures over time. The two most widely used methods for the analysis of K repeated measures for two groups are the K degrees of freedom (d.f.) T2 MANOVA F-test and the within-subjects 1 degree of freedom ANOVA F-test. Both require complete samples from normally distributed populations. In this paper, I describe alternative K and 1 d.f. distribution-free procedures which allow for randomly missing observations. These include a large-sample analysis of means, the Wei and Lachin multivariate Wilcoxon test with estimates of the Mann-Whitney parameter, and a multivariate Hodges-Lehmann location shift estimator based on the multivariate U-statistic of Wei and Johnson. Each of these methods provides a distribution-free K-variate estimate of the magnitude of group differences which can be used as the basis for an overall test of group differences. These tests include the K d.f. omnibus T2-like test, 1 d.f. tests of restricted hypotheses, such as the Wei-Lachin multivariate one-sided test of stochastic ordering, and the test of general association based on a minimum variance generalized least squares (GLS) estimate of the average group difference. I then describe covariate stratified-adjusted GLS estimates and tests of group differences. This approach also provides tests of homogeneity (interaction) for within-subjects and between-subjects effects. I illustrate these analyses with an analysis of repeated cholesterol measurements in two groups of patients, stratified by sex. Such analyses provide an overall distribution-free summary estimate and test of the treatment effect obtained by combining the group differences over both time (repeated measures) and strata.