TU-L0022 - Statistical Research Methods D, Lecture, 25.10.2022-29.3.2023
This course space end date is set to 29.03.2023 Search Courses: TU-L0022
Written assignment 4 (optional)
Readings
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A review and recommendations. The Leadership Quarterly, 21(6), 1086-1120. doi:10.1016/j.leaqua.2010.10.010
Video: https://www.youtube.com/watch?v=dLuTjoYmfXs (32:19)
Wooldridge, J. M. (2013). Introductory econometrics: a modern approach (5th ed.). Mason, OH: South Western, Cengage Learning. (Chapters 6-8, 9.5, 14.1, 17)
Hekman, D. R., Aquino, K., Owens, B. P., Mitchell, T. R., Schilpzand, P., & Leavitt, K. (2010). An Examination of Whether and How Racial and Gender Biases Influence Customer Satisfaction. Academy of Management Journal, 53(2), 238-264. doi:10.5465/AMJ.2010.49388763 (AMJ best paper winner for 2010)
Deephouse, D. L. (1999). To be different, or to be the same? It's a question (and theory) of strategic balance. Strategic Management Journal, 20(2), 147-166. doi:10.1002/(SICI)1097-0266(199902)20:2<147::AID-SMJ11>3.0.CO;2-Q
Mochon, D., Johnson, K., Schwartz, J., & Ariely, D. (2017). What Are Likes Worth? A Facebook Page Field Experiment. Journal of Marketing Research (JMR), 54(2), 306–317.
Optional
Rönkkö, M., Aalto, E., Tenhunen, H., & Aguirre-Urreta, M. (2020). Eight simple guidelines for improved understanding of transformations and nonlinear effects. Organizational Research Methods. https://doi.org/10.1177/1094428121991907
Antonakis, J., Bastardoz, N., & Rönkkö, M. (2019). On ignoring the random effects assumption in multilevel models: Review, critique, and recommendations. Organizational Research Methods. https://doi.org/10.1177/1094428119877457
Instructions
Read the listed material. You should understand the main principles discussed by Wooldridge, but you do not necessarily need to fully understand all the details or the equations. If you must choose, reading all four chapters quickly is preferable to reading just a part of the material in depth.
You can skim through the non-methodological parts of the three empirical papers. The versions available in the course Zotero library contain highlighted sections that are discussed in class. Note that both empirical papers are used in multiple classes so not all highlighted sections are discussed in the first class where a paper is used.
Questions
Please answer the questions in English. Answers written in other languages will not be graded.
1) Identify and explain in your own words at least three challenges to arguing causality based on section 3. "Why could estimates become inconsistent?” in the article by Antonakis and colleagues. How are the challenges that you address taken into consideration in the article by Hekman and colleagues or do they remain unaddressed?
2) Search definitions or explanations for following concepts in Part 1 (Chapters 2-9) and Chapter 17 in Part 3 of Wooldridge's book. Explain the concepts and how they are used in the empirical papers (Deephouse, Hekman et al, Mochon et al.). (Hint: Most, but not all concepts are used in the three empirical papers. Some concepts that are used are not obvious and it is OK to say that you did not find the concept used in the papers.)
More specifically, for each term or concept: a) Quote the definition from Wooldridge (remember page number) or if you cannot find an appropriate part to quote, explain on which page or pages Wooldridge explains the concept. b) Explain in your own words how you understood the concept and c) For each paper, state if the term or concept is being used or not. You need to also state which of the papers did not use a term or concept if you did not find it in the paper.
- Linear probability model
- Logit model (logistic regression)
- Maximum likelihood estimation (MLE)
- Log-likelihood
- Likelihood ratio (LR) test
- Poisson regression
- Average partial effect (APE) or average marginal effect (AME)
- Quasi-maximum likelihood estimation (QMLE)
- Cluster sample and cluster effect
- Dummy variable regression
- Within transformation
Submit your answers two days before the lecture and bring them also to the lecture. The answer should be 3-6 pages. If you have done this assignment as a part of a previous attempt at this course, you can use your old answer as a starting point and do a revision. If you need help or have questions about the assignment, please post those to the course forum.
Readings
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A review and recommendations. The Leadership Quarterly, 21(6), 1086-1120. doi:10.1016/j.leaqua.2010.10.010
Video: https://www.youtube.com/watch?v=dLuTjoYmfXs (32:19)
Wooldridge, J. M. (2013). Introductory econometrics: a modern approach (5th ed.). Mason, OH: South Western, Cengage Learning. (Chapters 6-8, 9.5, 14.1, 17)
Hekman, D. R., Aquino, K., Owens, B. P., Mitchell, T. R., Schilpzand, P., & Leavitt, K. (2010). An Examination of Whether and How Racial and Gender Biases Influence Customer Satisfaction. Academy of Management Journal, 53(2), 238-264. doi:10.5465/AMJ.2010.49388763 (AMJ best paper winner for 2010)
Deephouse, D. L. (1999). To be different, or to be the same? It's a question (and theory) of strategic balance. Strategic Management Journal, 20(2), 147-166. doi:10.1002/(SICI)1097-0266(199902)20:2<147::AID-SMJ11>3.0.CO;2-Q
Mochon, D., Johnson, K., Schwartz, J., & Ariely, D. (2017). What Are Likes Worth? A Facebook Page Field Experiment. Journal of Marketing Research (JMR), 54(2), 306–317.
Optional
Rönkkö, M., Aalto, E., Tenhunen, H., & Aguirre-Urreta, M. (2020). Eight simple guidelines for improved understanding of transformations and nonlinear effects. Organizational Research Methods. https://doi.org/10.1177/1094428121991907
Antonakis, J., Bastardoz, N., & Rönkkö, M. (2019). On ignoring the random effects assumption in multilevel models: Review, critique, and recommendations. Organizational Research Methods. https://doi.org/10.1177/1094428119877457
Instructions
Read the listed material. You should understand the main principles discussed by Wooldridge, but you do not necessarily need to fully understand all the details or the equations. If you must choose, reading all four chapters quickly is preferable to reading just a part of the material in depth.
You can skim through the non-methodological parts of the three empirical papers. The versions available in the course Zotero library contain highlighted sections that are discussed in class. Note that both empirical papers are used in multiple classes so not all highlighted sections are discussed in the first class where a paper is used.
Questions
Please answer the questions in English. Answers written in other languages will not be graded.
1) Identify and explain in your own words at least three challenges to arguing causality based on section 3. "Why could estimates become inconsistent?” in the article by Antonakis and colleagues. How are the challenges that you address taken into consideration in the article by Hekman and colleagues or do they remain unaddressed?
2) Search definitions or explanations for following concepts in Part 1 (Chapters 2-9) and Chapter 17 in Part 3 of Wooldridge's book. Explain the concepts and how they are used in the empirical papers (Deephouse, Hekman et al, Mochon et al.). (Hint: Most, but not all concepts are used in the three empirical papers. Some concepts that are used are not obvious and it is OK to say that you did not find the concept used in the papers.)
More specifically, for each term or concept: a) Quote the definition from Wooldridge (remember page number) or if you cannot find an appropriate part to quote, explain on which page or pages Wooldridge explains the concept. b) Explain in your own words how you understood the concept and c) For each paper, state if the term or concept is being used or not. You need to also state which of the papers did not use a term or concept if you did not find it in the paper.
- Linear probability model
- Logit model (logistic regression)
- Maximum likelihood estimation (MLE)
- Log-likelihood
- Likelihood ratio (LR) test
- Poisson regression
- Average partial effect (APE) or average marginal effect (AME)
- Quasi-maximum likelihood estimation (QMLE)
- Cluster sample and cluster effect
- Dummy variable regression
- Within transformation
Submit your answers two days before the lecture and bring them also to the lecture. The answer should be 3-6 pages. If you have done this assignment as a part of a previous attempt at this course, you can use your old answer as a starting point and do a revision. If you need help or have questions about the assignment, please post those to the course forum.
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