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The analysis of migration destinations is conducted using a conditional logit model that relates people's choices to the characteristics of the most selected destinations.
The stacked data was analysed using a conditional logit model.
We repeated the analysis using a conditional logit model without the respondents who chose the payment mechanism that was intended to be inferior in the fixed task choice set, as it is plausible (but not cogent) that these respondents gave invalid answers.
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However, whereas Kessler and McClellan (2000) used a conditional logit to model patient choices, we use a Poisson regression on aggregate GP-hospital flows, which is equivalent but is simpler to compute (Guimaraes et al., 2003).
As each question included a choice between three options ('scenarios' – two surveillance alternatives, and a no surveillance option) but only one could be chosen, we used a conditional logit model.
Under certain conditions, a conditional logit model [32] can be used to estimate this model, in which case the probability of selecting alternative j can be expressed as: Π nj = e x p θ ' Z j ∑ i e x p θ ' Z j (1).
In the current study, the calculation of coefficients was performed by conducting a conditional logit model using the maximum likelihood method being considered as the most appropriate methodological approach.
We pooled the choice data from two samples from the public who completed the questionnaire under scenario A and scenario B and estimated a conditional logit model using choice as the dependent variable.
For the DCE, a conditional logit model was used to estimate part-worth utilities for different attribute levels and assess the relative importance of each attribute [12].
A conditional logit model was used to analyse the choice response data.
Table 4 shows odds ratios (OR) based on a conditional logit model for choice of outpatient care for acute conditions (reference category: public healthcare providers).
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