Truncated Regression Model
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High Quality Content by WIKIPEDIA articles! Truncated regression models arise in many applications of statistics, for example in econometrics, in cases where observations with values in the outcome variable below or above certain thresholds systematically excluded from the sample. Therefore, whole observations are missing, so that neither the dependent nor the independent variable is known. Truncated regression models are often confused with censored regression models where only the value of the dependent variable is clustered at a lower threshold, an upper threshold, or both, while the value ...
High Quality Content by WIKIPEDIA articles! Truncated regression models arise in many applications of statistics, for example in econometrics, in cases where observations with values in the outcome variable below or above certain thresholds systematically excluded from the sample. Therefore, whole observations are missing, so that neither the dependent nor the independent variable is known. Truncated regression models are often confused with censored regression models where only the value of the dependent variable is clustered at a lower threshold, an upper threshold, or both, while the value for independent variables is available. One example of truncated samples come from historical military height records. Many armies imposed a minimum height requirement (MHR) on soldiers. This implies that men shorter than the MHR are not included in the sample. This implies that samples drawn from such records are perforce deficient i.e., incomplete, inasmuch as a substantial portion of the underlying population's height distribution is unavailable for analysis.
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