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Health Sciences Common Special Lecture IV, VIII

[https://minato.sip21c.org/ebhc/index-e.html] Latest update: 20 March 2024 (Wed)

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1. Aims of the lecture

For properly conducting health related research, basic knowledge of research design and statistics will be given.

In the year 2024, the class is given in hi-flex manner. Please refer BEEF+ system in detail.

In principle, the lecture is done in Japanese. Foreign students may ask the lecturer individually if necessary.

The text written in Japaneses [pdf format], latest version is on 8th April 2023 is freely available (Comments are welcome).

Caution! There is no lecture on June 12 and July 10.

2. Program

1. The very basics of health research (Apr 10, handout)
2. Basic terms in health/epidemiologic research (Apr 17, presentation, Practice)
3. Sample size issues (Apr 24, handout in English) (cf. E-learning course on ICRweb is useful.)
4. Research design (mostly experimental study design) (May 1, handout) [A review paper pdf for crossover design]
5. Data entry, missing data, graphical check, hypothesis testing, SD and SE (May 8, Excel format sample data)
6. Test of the location difference, test of proportion difference (May 15, handout in English)
7. Cross tabulation and its analysis, Kappa statistics, McNemar's test (May 22, handout, Bhapkar's test code)
8. ANOVA and Multiple comparison (May 29, handout)
9. Correlation, Regression and its application: Analysis of Covariance and Logistic Regression (June 5, handout)
10. Repeated measurement: Comparison of location parameters among 3 or more groups with corresponding data (June 19, handout)
11. Geographic information data analysis and spatial epidemiology (June 26, Special Lecture given online by Dr. Susumu Tanimura)
12. Evaluation of performances of diagnostic testing: ROC and Bland-Altman plot and the method to summarize systematic review: meta-analysis (July 3, handout for ROC and Bland-Altman plot, handout for meta-analysis)
    Example of meta-analysis: Is sperm concentration decreasing over the world?
    • The first paper written by Carlsen et al. (1992) in BMJ, which includes the data as table. According to the name of the research leader, so-called "Skakkebaek paper".
    • Reanalysis of the data in "Skakkebaek paper" by Swan et al. (1997)
    • Re-reanalysis of the data in "Skakkebaek papar" with newly added data by Swan et al. (2000)
    • New paper criticizing the "Skakkebaek paper" and followers about sampling bias written by Deonandan and Jaleel (2012)
    • New review paper (2016)�CNew cross-sectional study in Denmark (2018) by Prof. Skakkebaek's group.
    • New meta-regression paper by Dr. Swan's group (2017) (In addition, the supplementary material explaining the actual process of data collection and analysis is also available. However, downloading the data requires the password, available from the corresponding author.) (Interview to the first author is available) (Comments from professionals)
    • My web-log critics on "Skakkebaek paper" in 1998 (in Japanese), which has been later published in "Kagaku" journal by Iwanami-Shoten
    • Tab-delimited text file of the data in "Skakkebaek paper"
    • The R code to plot the data above as same graph as "Skakkebaek paper"
13. Survival analysis (handout in English�Cref. in Japanese) (July 17)
14. Experimental data analysis (on the other date, please see BEEF+)

3. Evaluation

Based on the end-of-term report of which theme is shown in BEEF+. Submit the report from BEEF+.

References

• (I strongly suggest the book, though written in Japanese) Toshiya Sato (2024) Space monster chipmunks learns more important issues than statistics. Asakura Shoten.
• Machin D, Campbell MJ, Walters SJ (2007) Medical Statistics, 4th ed., Wiley
• Lang TA, Secic M (2006) How to report statistics in medicine: Annotated guidelines for authors, editors, and reviewers. 2nd ed., American College of Physicians.
• Peacock JL, Peacock PJ (2011) Oxford handbook of medical statistics. Oxford Univ. Press
• Power and Sample Size (Vanderbilt University)
• EZR (Jichi Medical School)
• The lecture note for medical statistics at Gunma University written by Minato Nakazawa
• dfamefs.R: R code to calculate d-family effect size
• pooledr.R: R code to calculate pooled correlation coefficient using Fisher's Z transformation and weighed average

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