| They estimated the parameters of the model using a generalized linear model with a binomial error distribution and a probit link function. |
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| This distribution forms the base for the probit model, which is the model is used here. |
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| Thus, a multivariate probit analysis is utilized to examine the adoption of the four breeding technologies. |
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| The estimation of the probit and logit models including industry dummies was conducted in three steps. |
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| For example, cumulative per cent germination is probit transformed and then paired with the temperature-time at which the probit was observed. |
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| A probit model of binary choice was then used to assess the determinants of this employment probability. |
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| There are a couple of reasons for choosing the probit model over other models. |
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| The underlying statistical procedure applied is based on a parallel line assay and a classical probit model. |
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| The approximate curve for the power link approximating to the probit provides a fair approximation. |
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| As in the previous examination, the statistical analysis was performed using the probit method, to validate the results. |
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| They construct a statistical model, known as a probit equation, to determine which factors make victory more likely. |
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| For bluehead chubs and creek chubs we tested the hypotheses that probability of movement varied with size and growth using probit regression, pooling data over all months. |
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| First of all, the probit model is useful when the dependent variable is binary or limited to two outcomes. |
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| Given that there is no reason to prefer one over the other, we adopt the probit approach here. |
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| We estimate a discrete time survival model with a probit specification for house price expansions and contractions. |
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| These results are reported in Table A4 and A5, in Appendix 5 and 6, using a probit model. |
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| Indeed, when errors are heteroskedastic, probit estimates are inconsistent. |
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| The probit model utilizes the standard normal distribution in developing probabilities and is the additional method utilized in this analysis. |
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| Alternatively, assuming that happiness scores are ordinally comparable would justify the estimation with ordered probit or ordered logit. |
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| Two common choices are the logistic function which gives rise to a logit regression and the standard normal distribution function which yields a probit regression. |
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| The probabilities of consultation and the choice of the type of service were modelled, respectively, using probit and multinomial logit regressions. |
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| It is possible to generalize these findings by means of a probit regression model, where the independent variable is the candidate's lead in the polling average and the dependent one is whether he won or lost the state. |
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| Results based on weighted probit regression. |
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| The probit model uses the absolute value of the difference between 35 hours and the number of hours worked rather than the number of hours worked. |
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| Apart from scenarios in which fragments are in some cases liable to be thrown great distances, the translation of the physical consequences into physiological ones is generally performed by means of probit functions. |
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| To overcome this problem we introduced heteroscedastic extreme value model, probit model and mixed-logit model. |
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| We considered several specifications of the probit model. |
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