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By using a simulation approach, error in rate estimation can be isolated from the confounding problem of error in substitution model estimation present in empirical datasets.
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Worker and firm controls are included in each model estimation and presented in Table 8 in the Appendix.
Our approaches to model estimation are presented in section 3. The speech databases used in this paper are introduced in section 4. The experiments and the results obtained are presented and discussed in section 5. Finally, the conclusions are discussed in section 6.
Differences in HRQL between older and younger patients have been assessed with linear mixed-effect models and are shown as MDs in Tables 3 and 4. The effects of age group, time and group-by-time interaction from the first stage of model estimation are presented in Additional file 2: Table S2.
We used the restricted maximum likelihood (REML) as our model estimation method and present the estimated means and difference between treatments and their respective standard error means (SEs).
For comparison, the results of the beam lobe model estimation are also presented, based on the approach of a spatial moving least squares (MLS) method [21].
Section 4 presents model estimation results.
The presented model estimation results confirm the expectation that overall people show a general preference for car over public transport.
Based on the presented model estimation results, a key factor affecting the preference of respondents toward passenger car is the existence of parking space.
Table 3 presents the model estimation results for urban roads, while Table 4 presents the estimation results from rural roads.
For model estimation reasons, however, in the presented results there is one intercept presented, along with five threshold parameters (mu_1 through mu_5).
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