{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T10:02:48Z","timestamp":1790762568883,"version":"4.1.0"},"reference-count":22,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2006,10,12]],"date-time":"2006-10-12T00:00:00Z","timestamp":1160611200000},"content-version":"vor","delay-in-days":5704,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[1991,3]]},"abstract":"Abstract<\/jats:title>\n \n I describe a method for estimating and testing a threshold value in epidemiological studies. A threshold effect indicates an association between a risk factor and a defined outcome above the threshold value but none below it. An important field of application is occupational medicine where, for a lot of chemical compounds and other agents which are non\u2010arcinogenic health hazards, so\u2010alled threshold limit values or TLVs are specified. The method is presented within the framework of the logistic regression model, which is widely used in the analysis of the relationship between some explanatory variables and a dependent dichotomous outcome. In most available programs for this and also for other models the concept of a threshold is disregarded. The method for assessing a threshold consists of an estimation procedure using the maximum\u2010likelihood technique and a test procedure based on the likelihood\u2010ratio statistic\n R<\/jats:italic>\n , following under the null hypothesis (no threshold) a quasi one\u2010sided\n X<\/jats:italic>\n 2<\/jats:sup>\n distribution with one degree of freedom. This use of this distribution is supported by a simulation study. The method is applied to data from an epidemiological study of the relationship between occupational dust exposure and chronic bronchitic reactions. The results are confirmed by bootstrap resampling.\n <\/jats:p>","DOI":"10.1002\/sim.4780100306","type":"journal-article","created":{"date-parts":[[2007,4,26]],"date-time":"2007-04-26T07:49:20Z","timestamp":1177573760000},"page":"341-349","source":"Crossref","is-referenced-by-count":153,"title":["A statistical method for assessing a threshold in epidemiological studies"],"prefix":"10.1002","volume":"10","author":[{"given":"K.","family":"Ulm","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2006,10,12]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/ajim.4700140216"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.2307\/2529861"},{"key":"e_1_2_1_4_2","doi-asserted-by":"publisher","DOI":"10.1159\/000225106"},{"key":"e_1_2_1_5_2","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1080\/01621459.1973.10481353","article-title":"Fitting segmented polynomial regression models whose join point have to be estimated","volume":"68","author":"Gallant A. 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A.","year":"1980","journal-title":"International Statistical Review"},{"key":"e_1_2_1_13_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1977.10479935"},{"key":"e_1_2_1_14_2","volume-title":"The GLIM System","author":"Baker R. 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