1979
DOI: 10.1289/ehp.7932193
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Estimation of safe doses: critical review of the hockey stick regression method.

Abstract: The hockey stick regression method is a convenient method to estimate safe doses, which is a kind of regression method using segmented lines. The method seems intuitively to be useful, but needs the assumption of the existence of the positive threshold value. The validity of the assumption is considered to be difficult to be shown. The alternative methods which are not based on the assumption, are given under suitable dose-response curves by introducing a risk level. Here the method using the probit model is c… Show more

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Cited by 41 publications
(27 citation statements)
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“…The hockey stick model can treat a logtransformed outcome variable, as shown in Fig. 1, but can also provide a 95% lower confidence limit 28) ; regrettably, none of the studies cited in the present review calculated this 50,75) . Also, a model of multivariate regression could control for possible confounders such as age, inasmuch as the polynomial regression models are frequently used when the linear regression model does not fit well 28) .…”
Section: Methods For Estimation Of Critical Dosementioning
confidence: 82%
See 1 more Smart Citation
“…The hockey stick model can treat a logtransformed outcome variable, as shown in Fig. 1, but can also provide a 95% lower confidence limit 28) ; regrettably, none of the studies cited in the present review calculated this 50,75) . Also, a model of multivariate regression could control for possible confounders such as age, inasmuch as the polynomial regression models are frequently used when the linear regression model does not fit well 28) .…”
Section: Methods For Estimation Of Critical Dosementioning
confidence: 82%
“…We used P 0 of 5% and BMR of 5% as mentioned above, and the cutoff value for an average subject was computed by using the normalized value (i.e., [X i -X mean ]/SD) for each confounder (X i ). The BMD calculation, along with hockey stick regression analysis, i.e., a regression model using segmented curves 28) , was performed using the Statistical Package for the Biosciences (SPBS V9.54) 29,30) .…”
Section: Data Sources and Extractionmentioning
confidence: 99%
“…We tested each study year as a potential inflection point by fitting a model with separate linear slopes in the years preceding and the years after that point. 24,33 Within each plan and age group, the year for which the model had the smallest Akaike information criterion was designated the most likely year for a change in slope. If this 2-slope model fit significantly better than the single-slope model (P , .05), we calculated the percent year-to-year decline preinflection and postinflection.…”
mentioning
confidence: 99%
“…We used "hockey stick" regression 23 within each age group to fit 2 distinct linear trends over time. Briefly, this method allows detection of a deviation from a simple linear trend, by dividing the overall study period into 2 subperiods with different linear slopes.…”
Section: Discussionmentioning
confidence: 99%