1 of 39

BIOSTATISTICAL LITERACY: �What is it, and how can we teach it?

Featuring:

Michael Jiroutek

Campbell University

Laura Le

University of Minnesota

V.N. Vimal Rao

University of Illinois Urbana-Champaign

RSS Teaching Statistics Seminar Jan. 24, 2024

In collaboration with: Steve Foti (Univ. of Florida) and Ann Brearley (Univ. of Minnesota)

2 of 39

GOAL of Seminar

​

To promote a course that

develops students’ abilities to

read, interpret, and evaluate

evidence from data.

3 of 39

Laura Le

V.N. Vimal Rao

20

90

Student Background:

  • Public Health grad students
  • Health Science professionals (e.g., DNP, DVM, Dentists)

Class Format:

Online

Class Size:

to

Student Background:

  • Clinical research master’s students

25

Student Background:

  • Public Health undergrad students
  • Active duty military

8

40

8

Michael Jiroutek

Class Format:

In-person Online

Class Size:

to

Class Format:

Online

Class Size:

to

4 of 39

Laura Le

V.N. Vimal Rao

20

90

Student Background:

  • Public Health grad students
  • Health Science professionals (e.g., DNP, DVM, Dentists)

Class Format:

Online

Class Size:

to

Student Background:

  • Clinical research master’s students

25

Student Background:

  • Public Health undergrad students
  • Active duty military

8

40

8

Michael Jiroutek

Class Format:

In-person Online

Class Size:

to

Class Format:

Online

Class Size:

to

5 of 39

Laura Le

V.N. Vimal Rao

20

90

Student Background:

  • Public Health grad students
  • Health Science professionals (e.g., DNP, DVM, Dentists)

Class Format:

Online

Class Size:

to

Student Background:

  • Clinical research master’s students

25

Student Background:

  • Public Health undergrad students
  • Active duty military

8

40

8

Michael Jiroutek

Class Format:

In-person Online

Class Size:

to

Class Format:

Online

Class Size:

to

6 of 39

Warm-Up Questions

    • Go to pollev.com/vimalrao182
                • If you get a page that says “Register for Credit”, click Skip for now
    • (optional) Enter name on Introduce yourself
    • Answer each question on the page, clicking Submit button when done

Instructions:

Question #1:

What is statistical literacy?

Question #2:

Who should have it?

7 of 39

What is statistical literacy? Who should have it?

Definition (Ziegler & Garfield, 2018):

​

​

8 of 39

What is statistical literacy? Who should have it?

Definition (Ziegler & Garfield, 2018):

​

“The ability to read, understand, and communicate statistical information. This type of statistical information that is relevant for statistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics) is encountered in daily life, such as in a media article, and involves real contexts”.

​

​

9 of 39

What is statistical literacy? Who should have it?

Definition (Ziegler & Garfield, 2018):

​

“The ability to read, understand, and communicate statistical information. This type of statistical information that is relevant for statistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics) is encountered in daily life, such as in a media article, and involves real contexts”.

​

Who: Anyone who consumes media (Everyone!)

10 of 39

Identifying the Gaps

What’s missing?

​

​

​

​

11 of 39

Identifying the Gaps

What’s missing?

​

  • Necessary skills, knowledge, and ability for graduate students who will be data consumers

​

​

​

12 of 39

Identifying the Gaps

What’s missing?

​

  • Necessary skills, knowledge, and ability for graduate students who will be data consumers

​

​

What’s needed?

​

13 of 39

Identifying the Gaps

What’s missing?

​

  • Necessary skills, knowledge, and ability for graduate students who will be data consumers

​

​

What’s needed?

  • To read, interpret, and evaluate statistical results in peer-reviewed papers and abstracts

14 of 39

What is biostatistical literacy? Who should have it?

Definition: “The ability to read, understand, and communicate statistical information. This type of statistical information that is relevant for statistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics) is encountered in daily life, such as in a media article, and involves real contexts”

​

(Ziegler & Garfield, 2018)

​

​

15 of 39

What is biostatistical literacy? Who should have it?

Definition: “The ability to read, understand, and communicate biostatistical information. This type of statistical information that is relevant for biostatistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics) is encountered in daily life, such as in a media article, and involves real contexts”

​

​

16 of 39

What is biostatistical literacy? Who should have it?

Definition: “The ability to read, understand, and communicate biostatistical information. This type of statistical information that is relevant for biostatistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics, and study design) is encountered in daily life, such as in a media article, and involves real contexts”

​

​

17 of 39

What is biostatistical literacy? Who should have it?

Definition: “The ability to read, understand, and communicate biostatistical information. This type of statistical information that is relevant for biostatistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics, and study design) is encountered in research and scholarship, such as in academic journals and conferences, and involves real contexts”

​

​

18 of 39

What is biostatistical literacy? Who should have it?

Definition: “The ability to read, understand, and communicate biostatistical information. This type of statistical information that is relevant for biostatistical literacy (e.g., graphical representations, descriptive statistics, inferential statistics, and study design) is encountered in research and scholarship, such as in academic journals and conferences, and involves real contexts”

​

Who: Anyone who professionally consumes health-related information

​

19 of 39

Course Objective

Biostatistical Literacy has the primary goal of developing students’ ability to read and interpret statistical results in the primary literature of their specific scientific field of interest.

Includes

    • Critically reading research articles
    • Interpreting results

Does Not Include

    • Calculations (VERY minimal)
    • Statistical programming software (No!)

20 of 39

What is Biostatistics?

Branch of statistics that deals with data from biology, public health, Medicine, and other health sciences.

​

Examples:

•Identifying risk factors associated with a disease or condition

•Evaluating the effectiveness of interventions on a disease or condition

•Predicting disease or condition outcomes based on risk factors

21 of 39

Overview of Biostatistical Literacy Course

CI for a Mean

Summarizing Continuous Variables

CI for a Proportion

Intro to Survival Data

Intro to Biostatistics

Communicating Risk

Tests for Comparing Means/Hazards

Tests for Comparing Risks/Odds

Challenges in Statistics

Hypothesis Testing

Logistic and Proportional Hazards Regression

Multiple Linear Regression

Correlation & Regression

ANOVA

22 of 39

Overview of Biostatistical Literacy Course

Preparation

Read textbook and view online presentations

Complete Readiness Quiz

Active Learning

Concept Activity & Collaborative Key

Literature Activity & Collaborative Key

Assessment

Complete End-of-Unit Assessment

Early in Unit

Middle of Unit

End of Unit

UNIT TIMELINE

23 of 39

Example Unit: Introduction to Survival Data

​

​

Intro to Survival Data

Intro to Biostatistics

Collaborative Keys

Preparation

Read textbook and view online presentations

Complete Readiness Quiz

Active Learning

Concept Activity

Literature Activity

Assessment

Complete End-of-Unit Assessment

Early in Unit

Middle of Unit

End of Unit

24 of 39

Intro to Survival Data: Learning Objectives

Use these learning objectives as a checklist during the unit. After completing this unit, you should be able to:

​

  • explain what constitutes an “event”.
  • give examples of censored data.
  • identify starting date (i.e., “time zero”) for study participants.
  • identify summary measures of survival data analysis, such as median survival time and five-year

survival rate.

  • interpret a Kaplan-Meier survival curve, specifically:

o know what is on the x- and y-axes,

o know why the curve has steps,

o know what the curve tells you,

o be aware that censoring is taken into account in constructing the curve, and

o be able to indicate censoring on the curve.

​

​

​

25 of 39

Intro to Survival Data: Preparation

Preparation

Active Learning

Assessment

Read textbook and view online presentations

  • 1 to 4 chapters of Intuitive Biostatistics (by Harvey Motulsky, 2018, 4th ed.)
  • 1 to 3 recorded presentations

Complete Readiness Quiz

  • Formative assessments to help students check their understanding WHILE they are still learning
  • All multiple-choice or true-false question format
  • Low stakes, multiple attempts

​

​

26 of 39

Use small, imaginary cancer treatment study example (from textbook):

​

Goal: To understand how to properly account for censoring when estimating survival and what a Kaplan-Meier curve tells you.

Preparation

Active Learning

Assessment

Intro to Survival Data: Concept Activity

27 of 39

Activity: Provide step-by-step instructions for how to construct a survival curve with and without censoring to investigate impact.

Intro to Survival Data: Concept Activity

Preparation

Active Learning

Assessment

Example Questions

​

What is the event of interest?

​

What are some ways we can summarize or describe survival data?

​

Why is it important to include the censored data when carrying out survival data analysis?

​

Suppose your colleague needs help interpreting a Kaplan-Meier curve. How might you describe the characteristics and features of the curve?

​

Think of an example in your field of a time-to-event situation (that is not time-to-death). Be sure to specify what the event is.

28 of 39

Goal: To practice interpreting the results of survival analyses in the literature.

Preparation

Active Learning

Assessment

Intro to Survival Data: Literature Activity

Literature Article

29 of 39

Preparation

Active Learning

Assessment

Example Questions (General)

​

What is the authors’ primary research question/finding?

​

What sampling method and study design was used for this study?

​

What is the purpose of random assignment?

​

Do you think the comparison that the researchers did made sense or was appropriate? Why do you think they made this comparison?

​

What are some of the strengths/limitations of this study?

​

How qualified and reputable are the authors? Are there any potential conflicts of interest? What is the rank of the journal among journals in this field?

Intro to Survival Data: Literature Activity

30 of 39

Preparation

Active Learning

Assessment

Example Questions (Topic-related)

​

How is the event of interest defined? Where in the article does it say this?

​

How is time zero defined (e.g., starting date)?

​

How could a participant be censored in this study?

​

Examining the Kaplan-Meier curve, what do the two curves represent? Why do the curves not drop to 0% by the end? Which group has the best survival? Which group has the worst? Is there evidence of a difference between the two groups?

​

What is the estimated median survival time for a particular group?

​

What is the estimated 8-year survival for a particular group?

Intro to Survival Data: Literature Activity

31 of 39

Activities + Collaborative Keys

Preparation

Active Learning

Assessment

Activities: Students work independently or in groups

Students also work collaboratively as a class to create the “answer keys” for the activities via Google Documents. 

Instructor Engagement:

Teaching team [instructor(s), TAs] monitor the documents.

Activities

Instructor Engagement

Student Engagement

32 of 39

Contributions to Collaborative Keys

Ways to Contribute

  1. If blank, post an answer to a question. 
  2. If a question has a correct answer, but you think there are alternative correct answers, add your alternative. 
  3. If a question has an answer, but you think it is incorrect, add a comment and/or post what you think is the correct answer. 
  4. If a question has an answer, but you think the concept is confusing or needs additional explanation, ask a question OR provide a clearer explanation. 
  5. Post any additional thoughts you had while answering the question.
  6. Answer additional questions posed by the instructor or TAs.

Preparation

Active Learning

Assessment

33 of 39

34 of 39

Collaborative Keys: Benefits and Challenges

​

​

Preparation

Active Learning

Assessment

Benefits

  • Flexible, easy to implement
  • Low stakes
  • Quick feedback
  • Less time for faculty
  • Cooperative learning techniques
  • Builds learning community
  • ...and more!

Challenges

  • Quality of answers
  • Buy in (engagement) from students
  • Overambitious students

35 of 39

Intro to Survival Data: Assessment

Preparation

Active Learning

Assessment

Complete End-of-Unit Assessment

  • Summative assessments to help students evaluate their understanding at the END of the unit
  • All open-ended (short answer) question format (1-3 sentences, max)
  • 8-10 questions
  • “Higher” stakes than Readiness Quiz (but still low stakes on the whole), one attempt

36 of 39

Intro to Survival Data: Assessment

Preparation

Active Learning

Assessment

    • Identify the event of interest in this study.

​

    • What defines the starting date or time zero for a participant in this study?

​

    • Give one possible reason why a participant’s observation in this study might be censored

Provide real study abstract (slightly edited)

    • What is the estimated <time-X> survival for those in <group A>? Explain how you arrived at your answer.

​

    • What is the estimated median survival time for those in <group B>? Explain how you arrived at your answer.

Present Kaplan-Meier plot (from same study)

37 of 39

Conclusions

Biostatistical Literacy course offers a (flexible) approach for teaching students how to read and interpret statistical results in the research literature.

​

​

​

Different disciplines (e.g., swap out an article/context but use similar questions)

Course formats (in-person, hybrid, fully online)

Student populations

38 of 39

References

Brearley, A. M., Rott, K. W., & Le, L. J. (2023). A biostatistical literacy course: Teaching medical and public health professionals to read and interpret statistics in the published Literature. Journal of Statistics and Data Science Education.

Motulsky, H. (2018). Intuitive biostatistics: a nonmathematical guide to statistical thinking. Oxford University Press, USA.

Ziegler, L., & Garfield, J. (2018). Developing a statistical literacy assessment for the modern introductory statistics course. Statistics Education Research Journal, 17(2), 161-178.

​

39 of 39

Thank You!

RaoVNV.github.io/BiostatLiteracyProject

Michael R. Jiroutek

jiroutekm@campbell.edu

Laura Le

free0312@umn.edu

V.N. Vimal Rao

raovnv@illinois.edu

RSS Teaching Statistics Seminar Jan. 24, 2024