To test for randomization when Xi is binary,
A) you regress Xi,on all W's and compute the F-statistic for testing that all the coefficients on the W's are zero.(The W's measure characteristics of individuals,and these are not affected by the treatment. )
B) is not possible,since binary variables can only be regressors.
C) requires reordering the observations randomly and re-estimating the model.If the coefficients remain the same,then this is evidence of randomization.
D) requires seeking external validity for your study.
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Q2: The following is not a threat to
Q6: Your textbooks gives several examples of quasi
Q9: Experimental data are often
A)observational data.
B)binary data, in
Q10: The Hawthorne effect refers to
A)subjects dropping out
Q12: Experimental effects, such as the Hawthorne effect,
A)generally
Q14: A repeated cross-sectional data set
A)is also referred
Q15: In a quasi-experiment
A)quasi differences are used,i.e. ,instead
Q16: Causal effects that depend on the value
Q18: All of the following are reasons for
Q20: Heterogeneous population
A)implies that heteroskedasticity-robust standard errors must
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