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In order to improve the accuracy of results, Simar and Wilson [43] suggested the use of truncated regression with parametric bootstrapping, which can produce more consistent and efficient model coefficients.
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Statistics summary of Truncated regression models.
Some econometric models used in the one-step approach include Tobit and truncated regression models.2 For example, Omiti et al. (2009) use a truncated regression while Holloway et al. (2000, 2001a) and Martey et al. (2012) use Tobit models to model intensity of participation.
Using a truncated regression, the main inefficiency factors could be linked to the demographic characteristics of the households, as well as the proportion of income from rice as a proportion of total household income.
Given that we have discussed the rationale for also using a truncated regression model, we next describe the bootstrapping procedure to be used in this paper.
In comparison to that study, the present one employs several extensions to both the measurement of efficiency scores (using the Super-Efficiency DEA model) and the identification of their main determinants (using a bootstrapped truncated regression method) in order to yield more efficient and accurate results.
Then, the second step (steps 5 to 7 of Algorithm 2) is performed on STATA and consists in regressing the bias-corrected technical inefficiency scores over a set of exogenous covariates using a bootstrapped truncated regression with 1,000 iterations in order to obtain unbiased coefficients and confidence intervals.
This has necessitated the use of truncated logistic distribution truncated at point zero for modeling lifetime data.
The use of truncated guide RNAs also reduces off-target mutation frequencies (Fu et al. 2014).
Variables used in the truncated regression models included one dependent variable and eight independent variables recoded (see Additional file 1).
Consequently, some studies that have analysed quality of life data of this kind have used truncated regressions and censored least absolute deviations (CLAD) regressions [ 34, 35].
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