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In addition, we present a regulatory focus-based dummy regression model, which is a more general method that nests previous research on attribute-satisfaction as a special case.
This could not be achieved via conventional methods (eg, dummy regression analysis).
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Controlling for outliers in dummy regressions reveals that both the January and Monday effects turn from insignificant to highly significant.
The hourly dummy-regression model structure is given in Eq. 2: y_{i} = fleft( {text{expected hourly volume factor, temperature}} right)=beta_1EHVF+sum_{j=1}^6gamma_jCC_ij+xi_i (2)whEHVFEHVF is the expected hourly volume factor and others have the same definition with Eq. 1.
More formally, let the marginal effect of a TV channel dummy in regression (1) be δ 1 and the marginal effect of the same TV channel in regression (5) be δ 5.
The first two parts are deterministic parts and are modeled separately with dummy variable regression models.
The results for the dummy variable regression model in (1) are reported in Table 2.
The dummy variable regression model is estimated for the value-weighted (VW), equally-weighted (EW), and 10 decile portfolios sorted by market capitalization.
In a recent study, Roh et al. [5] conducted dummy variable regression modeling using vehicle classification data collected from WIM system.
The coefficient of the gender dummy in regression I captures the average gross gender employment gap that we saw in the earlier figures, and the time trend interacted with the gender dummy reflects the closing gender gap pattern.
This procedure is equivalent to dummy variable regression or analysis of covariance.
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