Consider the logit regression log(odds(QualExam)) = Bo + B1 * ParEduc + 62 * Awards. where QualExam is a binary variable that indicatespassing the exam if equal to 1, and failing the exam if 0, ParEduc indicates the parents' education level, and Awards is a binary variable that indicateshaving experience of obtaining award(s) if equal to 1, and not having experience if 0.Given the parents' average education level unchanged, the odds ratio is expected to beto those without awards. For an individual without awards and the parents' education level of 4, the estimated probability of passing the exam isapproximatelyfor an individual with awards to pass the exam comparingInterceptParEducAwards-10.532.980.48O A. 1.616; 80%.O B. 0.48; 4%.O C. 0.48; 80%.O D. 1.616; 4%.

Answered: Image /qna-images/answer/3d5f83bb-e5ce-44b4-9754-f4488f039541.jpg

Answered: for an individual with awards to pass…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 35EQ

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Consider the following panel model to examine the effect of retirement on consumption expenditure, consit, of individual i over years t=1,…,3: (B1) log⁡(consit) = β0 + β1retiredit + β2ageit + β3marriedit + β4healthit + δ1Yr2t + δ2Yr3t + ai + uit Where: retiredit is a dummy variable equal to 1 if individual i is retired on year t and 0 otherwise ageit is the individual's age in years marriedit is an indicator variable for whether the individual is married (1) or not (0) in year t healthit is an indicator variable equal to 1 if the individual is in 'good health' and 0 otherwise Yr2 is a dummy variable equal to 1 in year t=2 and 0 otherwise Yr3 is a dummy variable equal to 1 in year t=3 and 0 otherwise Using the information above, answer the following 3 questions. [i] Give two (2) examples of the kind of variables captured by the term ai in Model (B1). [ii] What is the crucial assumption we must make so that the random effects (RE) estimator is consistent? Under this assumption, why is…

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