Intermediate Econometrics Coursework Example | Topics and Well Written Essays - 2000 words

Intermediate Econometrics - Coursework Example permit and denote their unadjusted counterparts. ThenThe answer is FALSE in poundlinear regression analysis is used to severalize the pattern of data in a contingency table. A model is constructed to predict the natural log of the frequency of each cell in the contingency table. For a 2x2 table, that means the model is . So we endure always say, as a simple function, that the coefficient represents an increase in the log of predicted counts. If , for instance, we could say that this model shows that actor increases the predicted log count by 2 (all other factors held constant).The answer is TRUE all the third tests (Wald test, Lagrange Multiplier, likelihood ratio test) address the same basic question, which is, does constraining parameters to zero (i.e. leaving out the predictor variables) strike down the fit of the model? The null hypothesis for all three tests is that the smaller model is the true model, a large test statistics indicate that the null hypothesis is false. The only distinction between the tests is how they go well-nigh answering that question. The graph below explains more on the relationshipThe graph below illustrates what each of the three tests does. Along the (labelled ) are possible prises of the parameter . Along the are the values of the log likelihood corresponding to those values ofa. The test compares the log likelihoods of a model with values of the parameter constrained to virtually value to a model whereis freely estimated. It does this by comparing the height of the likelihoods for the two models to see if the difference is statistically significant (having in mind, higher values of the likelihood indicate better fit). In the habitus above, this corresponds to the vertical distance between the two dotted lines. In contrast, the Wald test compares the parameter estimateto whereis the value ofunder the null hypothesis, which generally states that. Ifis significantly different