probit


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probit

[′prō·bət]
(statistics)
A procedure used in dosage-response studies to avoid obtaining negative response values to certain dosages; five is added to the values of the standardized variate which is assumed to be normal; the term is a contraction of probability unit.
References in periodicals archive ?
Both hypotheses are possible, resulting in probit estimates of [[beta].
2011) conducted a review of the methodological tools employed for statistical analysis of crash injury severity, and found ordered logit and probit models, binary logit and probit models, and multinomial logit models to be the most common.
All probit and linear models used to estimate concentration distributions were fit using the lme4 package in R (Bates et al.
The paper is organized as follows: after the introduction, section 2 provides an overview of SMEs in Thailand; section 3 highlights a number of challenges faced by Thai SMEs; section 4 gives an overview of SME policies in Thailand; section 5 reviews the literature on the determinants of the decision by firms to export in the context of Thailand; section 6 provides an overview of the data collected from the ERIA-ISEAS survey; section 7 presents the analysis from Probit and Logit models; section 8 discusses the results; and section 9 concludes.
Although there was no measurement of natural mortality in non-treated earlier instars or eggs, it is assumed that natural mortality in these stages was also low and would not significantly affect the results of the probit analysis.
A Probit model is used because the restatement dependent variable is a dummy variable (binary) (Imai et al.
The assumed structure of the bivariate probit model and the Heckman selection model will account for the nonrandom sample problem (see Appendix A).
In the first stage separate probit models are fitted for each of the independent variables forming the univariate probit models and in the second stage all the independent variables added simultaneously into the probit model forming the probit model with multiple independent variables.
For a more accurate estimation of the model parameters, a probit regression analysis was also used assuming that at the infra optimum interval [[theta].