Syllabus

Learning outcomes

After the course, the student will understand the basic properties of three methods suitable for longitudinal and hierarchical data: panel regression, multilevel models, and (discrete) event history analysis. The student is able to read relevant methods literature and applied empirical research articles. The student is able to conduct their own research using at least one of the methods and communicate their results orally and in a written report.

• Understanding and managing longitudinal/multilevel data.
• Describing longitudinal/multilevel data.
• Formulating and answering an appropriate research question using longitudinal/multilevel data and appropriate methods.
• Using Stata for managing and editing longitudinal/multilevel data and estimating basic models for such data.

TIM as a learning platform

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The course website has embedded questions and other tasks. Try answering the first questions.

More information on working in TIM can be found at the end of the syllabus.

Schedule and work load

Course schedule

All sessions start a quarter past (for example, 12:15). Lectures and labs online. Seminars in Pub399.

Note also homework deadlines for each week/lab (during contact teaching):

• Preparations for lectures: before each lecture
• Weekly homework (for lectures): end of the respective week
• Lab homework: see the schedule

See a full list of homework and other deadlines here.

Workload

This is how much we expect your to work during the course.

Plan your schedule accordingly.

Pre-course assignment

Completed before the start of the course, including background information, video clips, readings, and drafting first ideas for own research (expected workload about 4–6 hours for Master students, 2–3 hours for PhD students).

Deadlines:

• Part A: 10 January at 10:00
• Part B: 16 January at 23:59

Find the instructions here.

Lectures, labs, and independent learning

The contact teaching is divided into three topics (blocks 1–3):

• Block 1: Panel regression (8 lectures, 4 labs),
• Block 2: Multilevel models (2 lectures, 1 lab), and
• Block 3: Event history analysis (5 lectures, 2 labs).

The lectures and labs run from 10 January to 10 March.

There is a break from lectures and labs after each block. The breaks are dedicated to revising the study material and to working on your own research topic. This is also the last chance to resubmit failed homework if you have been instructed to do so.

Each week we expect you to study independently approximately 4–7 hours, although the workload may differ between the weeks. First-year Master students should reserve (at least) 7 hours each week, PhD students and Master students close to graduation might do with 4–5 hours (depending on their previous studies and experience with quantitative methods and research).

Some tasks are to be completed before the corresponding lectures, some after, so plan accordingly.

Reports and seminar

Block 4 consists of own research. Students first submit a shorter research report, then present their work in a seminar, and finally develop their shorter report into a longer final report. Each student has an individual feedback discussion with a teacher after the course.

Workload for Master students

• 30 hours for short report, deadline 20 March.

• 5 hours for seminar presentation on 28–29 March.

• 55 hours for final report, deadline on 11 April.

• 15 minutes for individual feedback and discussion after the course.

Workload for PhD students

• 20 hours for short report, deadline 20 March.

• 3 hours for seminar presentation on 28–29 March.

• 21 hours for final report, deadline on 11 April.

• 15 minutes for individual feedback and discussion after the course.

Information on short report and final report.

Assessment and attendance

If you fall ill, have COVID-19 symptoms, have been exposed to COVID-19, or if you are in quarantine, you must not come to the university. You can miss one lab session without consequences (but you should complete the exercises as soon as possible).

Mandatory coursework consists of different tasks: weekly homework, lab work, seminar presentation, a short report, and a final report. The student needs to complete all tasks of the course adequately to pass the course as a whole (exception: short report is graded, but there is no threshold for passing).

The grade is based on reports (and possible bonus points). Other work is graded PASS/FAIL.

Both reports are graded by two teachers (main reviewer and backup reviewer).

Grading:

• 5 (excellent): 90–100 points
• 4 (very good): 80–89 points
• 3 (good): 70–79 points
• 2 (satisfactory): 60–69 points
• 1 (sufficient): 50–59 points
• 0 (failed): 0–49 points

Points and attendance are updated on the Grading page on the course website.

Final grades are given during the individual feedback discussions after the course.

Pre-course assignment

The pre-course assignment is mandatory and graded PASS/FAIL.

Homework

There are three types of homework: pre-lecture homework, weekly homework about lecture topics, and lab-related homework. Homework is intended to enhance learning and to divide the courseload more evenly throughout the course. Homework is mandatory.

Deadlines:

• Preparations for lectures (readings and quizzes): before each lecture
• Weekly homework: after lectures, but the end of the respective week
• Lab homework: midway or end of the respective block.

See the homework schedule for precise deadlines for the lab homework.

Homework is graded PASS/FAIL. Students may also earn bonus points that contribute toward their grade.

Labs

Attending the labs is necessary for being able to complete the coursework. Hence, attending the labs is mandatory.

If you are not able to attend a lab, you need to do the exercises (including interpretations) and submit your work for part A before the respective lab. Note that generally you will not get individual feedback regarding part A. You may, however, be asked to improve some parts of your work. Part B is the homework from the labs. See the homework schedule for information on the deadlines (1–2 in each block).

If you fall ill, you must not attend the lab onsite. You can miss one lab session without consequences (but you should complete the exercises as soon as possible).

If you miss several lab sessions and are not being able to submit the work for part A beforehand, exceptions to the rule are possible. Please provide a valid certificate (such as a doctor's note) if you wish to continue on the course.

Lab attendance and work is graded PASS/FAIL.

Short report

Short report on own research topic. Maximum of 20 points.

Short report makes 20% of the grade.

More information on requirements and its grading here.

Seminar

The seminar presentation and participation is graded PASS/FAIL.

Students may earn bonus points for active participation.

More information on the seminar and its grading here.

Final report

Longer report on own research topic. Maximum of 80 points.

The final report makes 80% of the grade.

More information on the final report and its grading here.

Individual feedback discussion

The individual feedback session (about 15 min) is mandatory but can be arranged onsite or online.

Bonus points

There are three ways of gaining a maximum of 8 bonus points:

• Homework bonus related to lecture preparations and weekly homework: 0.5–1 points for particularly well-formulated answers to open (written) questions
• Communication bonus related to communication in the course website: 1–2 points
• Seminar bonus related to giving constructive feedback to fellow students: 0.5–2 points

Bonus points are a bonus: it is possible to get full 100 points without any bonus points. These may, however, help to push a lower (passing) grade upward.

Bonus points will not help a student pass the course. In other words, they are only accounted for if the student gains at least 50 points from the reports and has completed all course work adequately.

Late or failed submissions or missed attendance

Homework is mandatory and their deadlines must be respected. If homework is submitted late, the teachers may not able to review and give timely feedback, which puts the student at risk of falling behind and failing their reports. The purpose of the homework not related to the report is to demostrate basic understanding of the other two topics, which is necessary for meeting the learning outcomes and passing the course.

Attendance in lectures is not mandatory, but highly recommended. If the student misses lectures they are responsible for studying the topics independently and to complete the in-class activities before the labs. Preparations before lectures and homework after lectures are both mandatory, irrespective of whether the student participates in the lectures or not.

Regarding attendance to the labs, students are entitled to one missed session without consequences. Lab homework is mandatory.

Late submissions of reports are allowed, as long as the student notifies the teachers and sets a new deadline for themselves. Late submissions reduce points by 1.5 points/day (approximately one grade per week).

Students must resubmit all failed or inadequate homework before the start of the next block the latest (unless instructed otherwise).

Because both the short report and the final report are a result of a gradual process with frequent feedback, resubmissions of reports are not accepted.

Correspondingly, a student may give only one seminar presentation (which must be of sufficient quality to pass).

If the student gets less than 50 points from the short and final report (combined), they will fail the course. The next chance to complete the course is when the course is offered again.

Students retaking the course will not get exemptions from coursework. They must complete and submit all assignments as new.

Learning environment, meetings, and communication

Lectures, labs, and independent work

Students are strongly encouraged to contribute to a positive learning environment. You are welcome to interrupt the teachers to ask questions or let them know if something is wrong, strange, or unclear.

All course materials are available on this site, either directly or as links.

Before lectures:

Before each lecture you will be assigned some pre-course homework including readings (textbook or methods articles) and related activities that typically test your understanding on some basic concepts and terms.

All homework is mandatory unless otherwise specified. You have one attempt with each quiz. At least 50% must be correct to pass. You may earn 0.5–1 bonus points for particularly well-formulated open answers (related to report work or other writing assignments).

During lectures:

The lecture meetings are a combination of lectures, discussions, and learning activities.

You can access the lecture material through the respective page for each lecture (access them through the navigation bar). This material includes in-class learning activities that you are to complete during the lectures. Please open the respective lecture material before each lecture.

Be respectful of others during all class time: be on time, use respectful language, and do not engage in unrelated conversations, social media, email etc. The teachers will do their best to keep the teaching engaging but we do need everyone's contribution!

Attending the lectures is highly recommended but not mandatory. The teachers will try to record the lectures but cannot guarantee it. If you are unable to participate in lectures, you need to complete the class activities at home before the labs.

Before labs:

The lab time is reserved for learning to use Stata and hands-on analyses, while the theoretical part is explained during lectures. Make sure you come prepared and understand the topics discussed during lectures. If you were not able to participate in the lectures, make sure to study the topics yourself and complete the lecture preparations before the lecture and in-class activities before the respective lab.

During labs:

Each lab starts with a joint part with an introduction to the relevant Stata codes and ends with independent working following detailed instructions and examples of how to run Stata code and help with interpreting the results.

Weekly homework:

In addition to the homework before the lectures, you will be assigned weekly homework that you should submit by the end of the respective week. These tasks include reading research articles and related activities, writing about methods as well as working on your own research topics.

The homework helps students getting familiar with how to write about, use, and interpret results from each method. You will practice formulating suitable research questions and the usage and interpretation of all methods. Eventually you will only write the report on one topic, but you need to demonstrate at least a basic understanding of each method to pass the course. Homework is graded PASS/FAIL.

The homework is the first step toward preparing for the research report and is a chance of getting feedback along the way. We recommend that you try to decide your topic and find a suitable dataset during the first week of the course so that you can benefit the most from your homework. You can warmly welcome to use the practice datasets.

Feedback

To help improve this course, students are asked to provide short anonymous feedback at the beginning of the course, after the first block, and at the end of the third block. This feedback will help the teachers to make changes for the benefit of their current students.

For general feedback and to help improve the course for the following year and all teaching in the programme, students will receive a link to the general MDPINVEST feedback questionnaire after the deadline of the final report. Students are encouraged to complete the general questionnaire before their individual feedback and evaluation discussion (scheduled after the submissions). The questionnaire is anonymous. The teachers will get the results after grades have been decided.

If at least 80% of the students answer to the final feedback questionnaire, all students receive a feedback bonus of 1 point.

Working in TIM

Navigating in TIM

There is a navigation bar on top of the page. Use it for accessing lectures, labs, report information, grading, and other course material.

The table of contents for this page can be found on the right-hand side.

Take a tour around the course website.

Email notifications

You can subscribe for email notifications for individual pages or for all pages in the course.

The subscription is done in the Manage tab which you can find on top of the page (see the figure below).

Check the relevant boxes in Notifications (see below). You can choose to get emails when someone makes edits on the page (document in TIM language), when someone posts new comments, or when someone edits their comments.

In the same place you can also opt for updates on edits to any document in the course: click on the link on the blue background (Subscribe to the entire folder).

Homework and in-class activities

There can be three kinds of activities in each lecture document.

See the pre-lecture homework at the start of the lecture document.

In-class activities are exercises that are completed during lectures. These appear in the middle of the lecture material and are completed as independent work or group work or together with the whole class.

Weekly homework is located at the end of the lecture document.

Note: Sometimes the questions are hidden from the reader (see the figure below). Instead of the question you might see a text "Open plugin" or a question without the space for answering. The solution is to hover your mouse over the "Open plugin" text or the place where the question should be.

Grading and feedback from homework

You can check the grading of homework from the Grading page.

It shows whether you passed the homework for a specific lecture or lab as a whole. Getting a 1 means that the quality of the homework was good enough. Value 0 means that you have not submitted the homework in time and value 0.5 means that your submission was incomplete or at least part of it needs to be revised.

Whether or not you passed, check your written answers for possible feedback such as clarifications, corrections of misunderstandings, or suggestions for how to improve the text for the report.

Generally we only give feedback on homework that was submitted before the deadline (unless we need you to revise the answer).

For checking points and feedback for a specific (written) answer, go back to the question. You see the points above the question. If you got a 0.5, we expect you to revise your answer.

You can check your feedback by clicking on the note in a colourful box on the right-hand side of the question. After clicking on the note, the full comment appears and you can also see which part of the text it refers to. Please read the comment and take the feedback into account when revising your answer and/or when working on your report. You can also leave comments below the feedback. See the figures below for examples.

You can submit the revised answer using the same place as the first version. Just save your answer again and it will show up as a new version. You can check all of your answers from the drop-down menu above the question. We will always comment on the latest answer available at the time of the review. Any comments are specific to the version of the answer.

Task summary

On top of the page you can find a task summary, which gives you information on the points earned and the number of completed tasks (questions in pre-lecture homework, in-class activities, and weekly homework).

Multiple choice questions are graded automatically and update automatically. Textual questions are graded by the teachers and will take some time to update in the task summary.

If the number of completed tasks is lower than the total even though you have completed answering, it may be an indication that you have missed a question (unless some questions were irrelevant in your case).

The task summary may be invisible until you start answering the questions. Refresh (F5) the page to update the task summary.

Check your task summary. How many tasks have you completed so far?

Saving TIM material and accessing TIM after the course

The TIM page will remain accessible to you for as long as you can log in using Haka with your current UTU id (or at least as long as TIM is accessible in general).

If you want to save the material for further reference, please remember that you are allowed to save it for your own use but not to redistribute it without permission.

The easiest way to save TIM material is to print each page as a PDF file (like you would print any html page, but choose for example PDF-XChange as the printer/destination instead of a printer).

Due to the accessibility legislation all video material must be subtitled if it is available for a year or longer. Because we have no resources to add subtitles, the videos are only visible for a limited amount of time. You can, however, download and save the recordings from Seafile for your own use.

Questions, comments, and discussions

The teachers write notes on the course discussion board. You can also use the discussion board to ask questions and discuss any topics relevant to the course. We encourage you to share useful tips and links to helpful study material with your peers.

Unless you plan to check the discussion board regularly, you may ask for email notifications to make sure that you receive teachers' notes in time. Click here and tick the relevant boxes under Notifications.

You can ask questions and add comments related to any course material (syllabus, notes, quizzes etc.) directly where you read it. Just click on the respective text section and a small grey box with a white pen appears on the right-hand side (it may be behind an orange or yellow bar if you have not yet marked the section read). Click on the pen, choose Comment/note and write your question or comment. (You can test this here on this page if you like.)

Note: anonymous comments and questions are not possible on this site. For private matters, send an email instead.

Email hours

For general questions, we recommend using the course discussion board or posting the question in the relevant page directly. Please use email for private matters only.

The teachers in this course are professional researchers whose main work is research.

The good thing is that we know a lot of interesting and timely research and topics that are relevant to social scientists.

The downside is that only 5% of our working time is recerved to teaching. This means that unfortunately we cannot be at your service at all working hours. For example, we cannot help you with a problem in your analyses the very last minute before a deadline. If the matter means work from our side (such as going through your analyses or Stata code) you must give us a few days to return to your inquiry. It is each student's responsibility to schedule their homework and work on the reports and seminar presentation accordingly.

Guidelines for commenting and discussing

If you have a question about the topics or the organization of the course, you are probably not the only one who would benefit from the answer. Perhaps you even find an error in the material (some of it is still very new). For this reason we would like to have all general questions and comments and their answers visible to all students.

We also know that many of our students are quite skilled at finding external resources relevant to learning. Please do share them with your fellow students!

We encourage active participation to the course by giving a communication bonus to the students who positively contribute to the course website.

Students gain 1 bonus point if they write at least 3 comments (questions, answers, or other helpful posts) to TIM (commenting material directly or using the discussion board).

Students gain 2 bonus points if they write 6 comments, of which at least 3 are answers to other students’ questions.

Only comments contributing towards learning count (Comments like “Thanks for the help” etc. are encouraged but not contributing toward learning).

When asking a question:

• Be precise. For example: “What do the dots mean in the formula for the between-unit variance?” instead of “I don’t understand between-unit variance”.
• Ask unrelated questions separately, in different comments or posts, so that others can find them easily.

When responding:

• It is good practice to give sources. For example: ”The dots refer to the dimension over which summation takes place. See the course book p. 76”.
• Read all relevant answers/comments before sending your own.

Sharing external material:

• Students are encouraged to share links to external material they find helpful. If you find a video, article, blog post etc. that helps you understand something, do share it with others!
• Always write at least a short description about the material and how it has helped you.
• If sharing anything else than links, make sure you have a right to do so (check licenses of pictures, cite the source of a quote etc.).

General instructions:

• The language of the course is English. Always write in English and use professional, proper language (as much as you can – we are mindful that English is not the first language to the majority of us). Explain any abbreviations you use.
• Be respectful. Avoid strong words, sarcasm, and creating tension. Racist, sexist, and other controversial comments are unacceptable. Posting inappropriate pictures or linking to inappropriate websites is not acceptable.
• Double check what you have written before posting.
• Do not waste other people’s time and effort. This includes unhelpful comments. This also means that deleting posts is not allowed (also your own; you may of course fix typos or clarify things).

Literature

Course textbook

Andreß, H. J., Golsch, K., & Schmidt, A. W. (2013). Applied panel data analysis for economic and social surveys. Springer Science & Business Media. (Available as an ebook through the library.)

Additional literature

Allison, P. D. (2009). Fixed effects regression models. SAGE publications.

Cameron, C. & Trivendi, P. (2009): Microeconometrics using Stata. Texas: Stata Press.

Elwert, F. & Winship, C. (2014): Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable. Annual Review of Sociology, 40, 31-53.

Heisig, J. P. & Schaeffer, M. (2019): Why You Should Always Include a Random Slope for the Lower-Level Variable Involved in a Cross-Level Interaction. European Sociological Review, 35, 258–279.

Ludwig, V. & Brüderl, J. (2018): Is There a Male Marital Wage Premium? New Evidence from the United States. American Sociological Review, 83(4): 744-770. doi:10.1177/0003122418784909

Mood, C. (2010). Logistic regression: Why we cannot do what we think we can do, and what we can do about it. European sociological review, 26(1), 67-82.

Rabe-Hesketh, S. & Skrondal, A. (2012): Multilevel and Longitudinal Modeling Using Stata. Third edition (Volume I: Continuous Responses; Volume I & II). Texas: Stata Press

Vella, F., & Verbeek, M. (1998). Whose wages do unions raise? A dynamic model of unionism and wage rate determination for young men. Journal of Applied Econometrics, 13(2), 163-183.

Winship, C. & Morgan, S. L. (1999): The estimation of causal effects from observational data. Annual Review of Sociology, 25, 659-706.

Wooldridge, J. (2012): Introductury Econometric. A modern Apporach. Fifth edition. Mason: South Western