PSY-564
psy564

Session: Spring 2015 (Jan 6 - Apr 2)
Meeting Time: TF 12:30 a.m. -13:50 p.m.
Meeting Place: HSD A160

Instructor Dr. Scott M. Hofer Dr. Andrey Koval
Office Cornett A271 Cornett B335g
Hours By appointment By appointment
Email smhofer at uvic dot ca andkov at uvic dot ca
Phone 853-3862 472-4864

Class meets twice a week. On Tuesdays will focus on conceptual understanding of the processed material, whereas Fridays will be dedicated to development of practical skills in reporting statistical models.

Meeting Week Class Topics Chapter Report due (23:59)
06 Jan 1 1 Introduction to Multilevel Models for Longitudinal and Repeated Measures Data H-1
09 Jan 2
13 Jan 2 3 Interpreting General Linear Models H-2
16 Jan 4 Markdown chapters review
20 Jan 3 5 Introduction to Within-Person Analysis and RM ANOVA H-3
23 Jan 6 R-Cheatsheet
27 Jan 4 7 Introduction to Random Effects of Time and Model Estimation H-5
30 Jan 8 Reporting models
03 Feb 5 9 Introduction to Random Effects of Time and Model Estimation H-5
06 Feb 10 Random Coefficients Models
10 Feb 6 Reading Week
13 Feb Reading Week
17 Feb 7 11 Describing Within-Person Change H-6
20 Jan 12 Describing shape of WP change
24 Feb 8 13 Time-Invariant Predictors in Longitudinal Models H-7
27 Feb 14 Time invariant predictors
03 Mar 9 15 Analysis of Repeated Measures Designs not Involving Time H-8
06 Mar 16 Daily diary studies
10 Mar 10 17 Time-Varying Predictors in Models of Within-Person Fluctuation H-9
13 Mar 18 Time variant predictors
17 Mar 11 19 Multilevel Models for Clustered Data RB-5
20 Mar 20 Clustered structures
24 Mar 12 21 Evaluating Alternative Metrics of Time H-10
27 Mar 22 Alternative metrics of time
31 Mar 13 23 Final
03 Apr 24 Wrap Up

Note: H - Hoffman, RB - Raudenbush & Bryk

The course has been design in the “flipped classroom” format. Instead of listening to lectures during class periods, the learners will work through lectures (prepared in advance) on their own. The course content for each week will be availible via three media:

All three media were produced by Lesa Hoffman. This course will closely follow her course.

Texts

Required
- Longitudinal Analysis: Modeling Within-Person Variation and Change (Lesa Hoffman, 2014).

Recommended

Mission Statement

This course will provide an overview of current statistical approaches for the analysis of variation and change. Conceptual and research design issues will be discussed throughout with an emphasis on alternative models for explaining and predicting individual-level change. Hands-on training in analysis of longitudinal data will focus on use of Mplus, SAS, and R, comparing and exploring features of both traditional MLM and SEM approaches. A variety of models will be examined and applied to actual data including models with time invariant and time-varying covariates, factor-level outcomes, alternative time structures, and joint models of variation and change. Substantive examples will be used throughout the course based on published and unpublished results from several major longitudinal studies on developmental and aging-related change.

Evaluation and Grading Policy

Course evaluation will be based on the ability to independently analyze data, correctly interpret model estimates, and effectively communicate and discuss results. The assignments are designed to provide experience with model conception and specification, evaluation of model fit and nested models, interpretation of results, and communication of research findings.

Throughout the semester you will be earning course points which will be used to compute the total percent score. The total of 200 points will come from participating in the class activities, producing dynamic reports, and taking the final examination.

what when number of points each total points
In-classs activities Tuesdays 10 8 80
Report Fridays 10 10 100
Final March 31 1 20 20
Total 200

The final letter grade in the course will be based on total percent score rounded to the third decimal point as shown in the table:

Grade Lowest Highest Description
A+ 90 100 Exceptional Work Technically flawless and original work demonstrating insight, understanding and independent application or extension of course expectations; often publishable.
A 85 89 Outstanding Work Demonstrates a very high level of integration of material demonstrating insight, understanding and independent application or extension of course expectations.
A- 80 84 Excellent Work Represents a high level of integration, comprehensiveness and complexity, as well as mastery of relevant techniques/concepts.
B+ 77 79 Very good work Represents a satisfactory level of integration, comprehensiveness, and complexity; demonstrates a sound level of analysis with no major weaknesses.
B 73 76 Acceptable work that fulfills the expectations of the course Represents a satisfactory level of integration of key concepts/procedures. However, comprehensiveness or technical skills may be lacking.
B- 70 72 Unacceptable work
C+ 65 69 Unacceptable work
C 60 64 Unacceptable work
D 50 59 Unacceptable work
F 0 49 Failing grade Unsatisfactory performance. Wrote final examination and completed course requirements.

How this will work

There are the total of 13 weeks in the semester. Every week (except for the first, the reading week, and the last) 18 points can be earned: 10 points from a dynamic report and 8 points from class participation.

Dynamic reports will be turned in electronically before 11:59 pm on the Friday the week they are due.

Class participation involves two type of activities: recurring and wildcards. Recurring activities are: quiz question, guess page, guess slide, and Rosetta Stone.

Quiz Question Please write the question about the content of the current chapter/lecture that you think should appear on the final exam? Post Anonymously into the corresponding comment thread on the page for the current week of the course.

Guess Page In the current chapter, what page contains one of the most important ideas or concepts? Provide the page number and the answer why in less than 140 characters, omg, no abbr plz! Post Anonymously into the corresponding comment thread on the page for the current week of the course.

Guess Slide In the current lecture, what slide contains one of the most important ideas or concepts? Provide the slide number and answer why in less than 140 characters, omg, no abbr plz! Post Anonymously into the corresponding comment thread on the page for the current week of the course

NOTE Quiz Quesion, Guess Page, and Guess Slide must be submitted into the respective comment threads no later that 10:30 am of the Tuesday of the current week.

Rosetta Stone A question, a series of questions, or other activity that involves learning some programming language or comparing programming languages.

The activities for the other 4 class participation points will be wildcards - you will not know what they will be ahead of time to keep things interesting.

Extra Credit
In addition, each week learners will have the opportunity to earn up to two (2) points of extra credit:

Prerequisites

This is an advanced course on research methodology and statistical analysis. Students should have familiarity with multivariate statistical methods (e.g., multiple regression, factor analysis). Experience with Mplus, SAS, or R is beneficial, but not expected. Please contact the instructor if you have questions about these prerequisites.

Important Course Policy Information

Commitment to Inclusivity and Diversity

The University of Victoria is committed to promoting, providing and protecting a positive and supportive and safe learning and working environment for all its members.

Academic Integrity

The Department of Psychology fully endorses and intends to enforce rigorously the Senate Policy on Academic integrity(p. 33-34, UVic Calendar 2014-15). It is of utmost importance that students who do their work honestly be protected from those who do not. Because this policy is in place to ensure that students carry out and benefit from the learning activities assigned in each course, it is expected that students will cooperate in its implementation.

The offences defined by the policy can be summarized briefly as follows:

  1. Plagiarism. You must make sure that the work you submit is your work and not someone else’s. There are proper procedures for citing the works of others. The student is responsible for being aware of and using these procedures.
  2. Multiple Submission. Only under exceptional circumstances may a work submitted to fulfill an academic requirement be used to satisfy another similar requirement. The student is responsible for clarifying this with the instructor(s) involved.
  3. Falsifying Materials Subject to Academic Evaluation. This includes falsification of data, use of commercially prepared essays, using information from the Internet without proper citation, citing sources from which material is not actually obtained, etc.
  4. Cheating on Assignments, Tests, and Examinations. You may not copy the work of others in or out of class; you may not give your work to others for the purpose of copying; you may not use unauthorized material or equipment during examinations or tests; and you may not impersonate or allow yourself to be impersonated by another at an examination. The Department of Psychology has a policy of not making old examinations available for study purposes. Therefore, use of old exams without the express written permission of the instructor constitutes cheating by the user, and abetting of cheating by the person who provided the exam.
  5. Being an Accessory to Offences. This means that helping another student to cheat (for instance, by showing or communicating to them answers to an assignment, or by allowing them to view answers on an exam) is an academic offence.