Simpson's Paradox

Simpson's Paradox

Simpson's paradox (or the Yule-Simpson effect) is an unexpected result in which a association/correlation of  x and y in different groups disappears or reverses when the groups are combined.

• Wikipedia. Simpson's paradox and other Statistical paradoxes
• Simpson's Paradox
• Bob Horton (2015). Fun with Simpson's Paradox: Simulating Confounders
• Natloff (2014). Simpson's paradox is back
• Revolutions (2013). An interactive tool to explain Simpson's Paradox
• Tu (2008). Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox
• Baker (2001). Good for women, good for men, bad for people
• Taylor (2014). Simpson’s Paradox: A Data Set and Discrimination Case Study Exercise

uncertainty

When scientist and policy maker plus uncertainty

• Schmitt (2014). "The Pitfall of Uncertainty" (The Scientist)
• The Scientist published an opinion article about what uncertainty means to scientisit and policy maker. "...they must be crystal clear: science is about discovery and (decreasing) uncertainty, policymaking is about achieving consensus (if not certainty). Together, scientists and policymakers alike must strive to make responsible decisions for the benefit of society."
• NPR (2017). Alan Alda's Experiment: Helping Scientists Learn To Talk To The Rest Of Us
• Wikipedia:
  • Truth
  • Certainty
  • Wikiquote. Truth
• A intuitive figure of true vs truth of Starecat.com: This is TRUE, this is TRUE, this is TRUTH. I like this figure indeed. However, 'True' is a an adjective; 'truth' is a noun. I would like to change this into "This is TURE, this is TURE, this is THE THUTH" or "This is a FACT, this is a FACT, this is THE TRUTH"

    

Proposed Revisions to the Common Rule

Proposed Revisions to the Common Rule for the Protection of Human Subjects in the Behavioral and Social Sciences

It examines how to update human subjects protections regulations so that they effectively respond to current research contexts and methods. With a specific focus on social and behavioral sciences, this consensus report aims to address the dramatic alterations in the research landscapes that institutional review boards (IRBs) have come to inhabit during the past 40 years. The report aims to balance respect for the individual persons whose consent to participate makes research possible and respect for the social benefits that productive research communities make possible... (full text)

How to organizing a scientific meeting

How to organizing a scientific meeting

• Goldberg (2001). Another thing they never taught you in grad school: How to organize a scientific meeting
• Corpas (2008). Ten Simple Rules for Organizing a Scientific Meeting.
• IAPSS. How to organize a conference step by step manual (pdf)
• Rivlin (1995). Guide to organizing an international scientific conference (Google Book)
• Brett (2009). How to run a meeting
• What is the best way to start a meeting?
• Beare. Useful English phrases for participating in a business meeting. Phrases for performing well in busines meetings.
• EnglishClub. Meetings in English
• Reinhart (2013). Giving an introduction speech
• Reeves. How to close a meeting
• Robert (1876): Robert's Rules of Order for fair and orderly meetings & conventions
• The Robert's Rules Process for Handling a Main Motion
• Parliamentary Procedure for Meetings

Unconventional view of type 2 diabetes causation proposed

Unconventional view of type 2 diabetes causation proposed
Source: MedicalPress

At 85, Nobel laureate James D. Watson, the co-discoverer of the double-helix structure of DNA, continues to advance intriguing scientific ideas. His latest, a hypothesis on the causation of type 2 diabetes, is to appear 7 pm Thursday US time in the online pages of The Lancet, the prestigious British medical journal.
 
Watson's hypothesis suggests that diabetes, dementias, cardiovascular disease, and some cancers are linked to a failure to generate sufficient biological oxidants, called reactive oxygen species (ROS). Watson also argues the case for a better understanding of the role of exercise in helping to remedy this deficiency. ...
 

Tips - EndNote

EndNote

Tutorial

• EndNote Training on YouTube
• FAQs
• EndNote user's manual

Entering and Editing Reference

• When entering initials instead of full names, be sure to type a period (.) or a space between initials:
  Fisher, J.O.
  O Fisher
• When entering corporate authors, put a comma (,) after the name:
  U.S. Department of Agriculture,
  Apple Computer Inc.,

Bibliographic Styles (Output Style)

• EndNote Reference Style Files
• Wiley-Blackwell Author Services
• Reference Style Files by EndNote has a lot of files but some are out-of-date. For example, Diabetes Care style file was published on 8/17/2006 (accessed on 01/06/2012).
• I created an EndNote output style file for Diabetes Care (file name: Diabetes_Care_YC.ens date: 10/01/2012)
• How to set Hanging Indent
• Helps of Endnote about "Hanging indent" options is not so helpful. The options (from a dropdown) is hidden in the right-low corner after you go through the menu "Edit - > Output Styles -> Bibliography -> Layout". It can be missed easily. The options include: None, All Paragraphs, First Paragraph Only, Second Paragraph Only, and All Paragraphs but the First.
• If you are creating a numbered bibliography, you need insert a tab after the bibliography number to have the references line up correctly. (You need use "Insert Field" of a dropdown in the up-right corner to insert a tab)
• In the MS Word, the Tab size (even the hanging indent) can be changed by select all the bibliography and slide the ticks of ruler.
• How to change line space of your bibliography (I hate to say that this is not a logic/intuitive way)
• In EndNote (please don't be confused the 'Cite While You Write' in MS Word), go to Tools>Cite While You Write>Format Bibliography, then the EndNote will open a Window 'Configure Bibliography' of MS Word, click 'Layout' tab, you can change the line spacing there.
• Or, in the MS Word document, select the 'Endnote' tab, clicking the small arrow at the corner of the 'Bibliography' block, then click 'Layout' tab. It may take minutes to active it, then you change the bibliography format there.
• The solution provided by the EndNote website is not so clear.
• Special Formatting Characters for Templates:
  • o Ctrl+Alt+Space (non-breaking space or from the Insert field list): linking adjacent text, e.g. Edition◊ed.
  • | (vertical bar): forcing separation, e.g. Author. ·"Title."·Journal Volume|.Issue|·(Year)|:· Pages|
  • `xxx`(on the same key as the tilde (~)):forcing EndNote to interpret a word between them as just text and not as a field name, e.g. (Editor) vs. (`Editor`)
  • ^ (caret): the lable before the pages should appear in plural or singular form depending on the number of pages, e.g. p^pp◊Pages.
• How to Get Endnote to Abbreviate Journal Names: Journal Term List.
• How to reset EndNote Web library
• More FAQs of The University of Toledo
• When convert the X9 library into 20 library, if you lost files, try: The proper process for recovering library files

When you online search PubMed in the EndNote, the record includes the URL for PubMed articles. However, quite annoying, when the PubMed.com outputs a file for citation manager, there is no URL information. You need highlight the EndNote records in your library and go to "References" menu => "Find Reference Update".

Need more statins or not

Need More Statins or Not

2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults

Don’t Give More Patients Statins
Source: NYT by John Abramson and Rita Redberg

"ON Tuesday, the American Heart Association and the American College of Cardiology issued new cholesterol guidelines that essentially declared, in one fell swoop, that millions of healthy Americans should immediately start taking pills — namely statins — for undefined health “benefits.” " ...

New ACC/AHA/NHLBI Guidance on Lifestyle for CVD Prevention
Source: Medscape by Shelley Wood

ACC-AHA cardiovascular prevention guidelines drop cholesterol treatment goals
Source: Cardiology News Digital Network  by Elizabeth Mechcatie

Risk Calculator for Cholesterol Appears Flawed
Source: NYT by Gina Kolata
"Last week, the nation’s leading heart organizations released a sweeping new set of guidelines for lowering cholesterol, along with an online calculator meant to help doctors assess risks and treatment options. But, in a major embarrassment to the health groups, the calculator appears to greatly overestimate risk, so much so that it could mistakenly suggest that millions more people are candidates for statin drugs." ...

Speaking Stata of the Stata Journal

Speaking Stata of the Stata Journal

Blog: Stata Tips of The Stata Journal and Others

This column of the Stata Journal is focusing on how to improve your fluency in Stata

1. Loops, again and again [20(4)]
2. Is a variable constant?
3. More ways for rowwise
4. Concatenating values over observations
5. Some simple devices to ease the spaghetti problem
6. The last day of the month
7. How best to generate indicator or dummy variables
8. Seven steps for vexatious string variables
9. From rounding to binning
10. Logarithmic binning and labeling
11. Tables as lists: The groups command
12. Letter values as selected quantiles
13. Shading zones on time series and other plots
14. Multiple bar charts in table form
15. Truth, falsity, indication, and negation
16. A set of utilities for managing missing values 
17. Species of origin [15(2)]
18. Design plots for graphical summary of a response given factors
19. Self and others
20. Trimming to taste
21. Creating and varying box plots: Correction
22. Matrices as look-up tables
23. Axis practice, or what goes where on a graph
24. Transforming the time axis
25. Output to order
26. Fun and fluency with functions
27. Compared with ...
28. MMXI and all that: Handling Roman numerals within Stata
29. Graphing subsets
30. The limits of sample skewness and kurtosis
31. findname: Finding variables
32. statsby [subsets, total]: The statsby strategy
33. graph twoway: Paired, parallel, or profile plots for changes, correlations, and other comparisons
34. graph box: Creating and varying box plots; Creating and varying box plots: Correction
35. qsbayesi, qsbayes: I. J. Good and quasi–Bayes smoothing of categorical frequencies
36. egen, rowsort, rowranks: Rowwise
37. distinct: Distinct observations
38. corrci, corrcii: Correlation with confidence, or Fisher's z revisited
39. labmask, seqvar: Between tables and graphs
40. Spineplots and their kin
41. egen, by: Counting groups, especially panels
42. stem, scatter, stemplot: Turning over a new leaf
43. egen, by: Identifying spells
44. count: Making it count
45. In praise of trigonometric predictors
46. cycleplot, sliceplot: Graphs for all seasons
47. Time of day
48. Smoothing in various directions
49. qplot, displot: The protean quantile plot
50. Density probability plots
51. modeldiag: Graphing model diagnostics
52. Graphing agreement and disagreement
53. Graphing categorical and compositional data
54. Graphing distributions
55. matrix list, list, tabdisp, tabcount, groups: Problems with tables, Part II
56. tabulate, table, tabstat, tabdisp, list: Problems with tables, Part I
57. for, foreach, forvalues, levels: Problems with lists
58. egen, foreach, forvalues, reshape: On structure and shape: the case of multiple responses
59. egen: On getting functions to do the work
60. On numbers and strings
61. foreach, forvalues, for: How to face lists with fortitude
62. _n, _N: How to move step by: step
63. How to repeat yourself without going mad [2001;1:(1)]

Measures of effect size in Stata 13

Measures of Effect Size in Stata 13
Soruce: the Stata Blog
"Today I want to talk about effect sizes such as Cohen’s d, Hedges’s g, Glass’s Δ, η2, and ω2. Effects sizes concern rescaling parameter estimates to make them easier to interpret, especially in terms of practical significance.

Many researchers in psychology and education advocate reporting of effect sizes, professional organizations such as the American Psychological Association (APA) and the American Educational Research Association (AERA) strongly recommend their reporting, and professional journals such as the Journal of Experimental Psychology: Applied and Educational and Psychological Measurement require that they be reported.

Anyway, today I want to show you

What effect sizes are.
How to calculate effect sizes and their confidence intervals in Stata.
How to calculate bootstrap confidence intervals for those effect sizes.
How to use Stata’s effect-size calculator.

...". Read full text here

11 Tips to Cut Your Cholesterol Fast

True

11 Tips to Cut Your Cholesterol Fast

Source: WebMD By Laura J. Martin, MD

 

1. Set a target.

2. Consider medication.

3. Get moving.

4. Avoid saturated fat.

5. Eat more fiber.

6. Go fish.

7. Drink up.

8. Drink green.

9. Eat nuts.

10. Switch spreads.

11. Don't smoke.

 

Full text here.

 

Asians Eat Weird Things

Asians Eat Weird Things 

Debating obesity the disease

Debating obesity the disease
Source: MedScape

Follow the Money?

Fat Equals Sick: Is This About the Money?
Getting Paid for Treating Obesity, Now That It's a Disease
AMA: Diagnosis by Majority

Is It an Addiction? Can Obesity Be an Addiction?

Also Weighing in on the Disease Debate Obesity: It's a Risk! It's a Symptom! It's a Disease!
Obesity as a Disease? 'It's Academic'

News Behind the Perspectives AMA Declares Obesity a Disease
Obesity Disease Classification Will Help With Treatment, Docs Say

How to turn on/off and diagnose the ANC (active noise cancellation) system of 2013 Honda Pilot

How to turn off/on the ANC (active noise cancellation) system of 2013 Honda Pilot

1. Turn the ignition switch on the I (radio) position.
2. Turn the radio on and check it operates normally, and turn the radio off.
3. Press and hold the preset buttons #1, #6, and volumn (VOL) push button at the same time.
4. when you see 'DIAG' appears on the display, you can release the buttons
5. Press the #1 preset button, you see 'ANC ON' on the display.
6. Press the #1 preset button again to turn the ANC OFF and hear a humming/booming noise coming from the speakers for about 1 minutes.
7. You can press the #1 button repeatedly for ON and OFF, but the humming/booming noise will not come up repeatedly except repeating step 1, 3-6 again.

This is a similar approach for Acura

Data visulization - a tutorial

Data visulization - a tutorial
Source: Tyler Rinker's blog

This is a nice video about how to visualize your data more effectively.

You can find the whole blog with slides and data here: The Mechanics of Data Visualization.

How to test proportionality assumption in survival analysis using SAS

How to test proportionality assumption in survival analysis using SAS

 

There are several approaches to test proportionality assumption in survival analysis:

• Graphical Approach is to plot Log–Log survival function by researched major predictor. If the two line is parallel without cross each other, the assumption is considering confirmed.

PROC LIFETEST DATA=ONE; METHOD=KM PLOTS=(S,LLS);
     TIME SURVTIME*EVENT(0);
     STRATA RISK0;
RUN;

PROC PHREG DATA=ONE;
     MODEL SURVTIME*EVENT(0)=RISK1 AGE SEX;
    BASELINE OUT=LLSOUT LOGLOGS=LOGLOGS;
RUN;
PROC GPLOT DATA=LLSOUT;
     PLOT LOGLOGS*SURVTIME=RISK1;
RUN;

• Or, you can include an interaction term of a predictor and follow up time in the model. If this interaction term is not significant, there is no violation of assumption. For example:

PROC PHREG DATA=ONE;

MODEL SURVTIME*EVENT(0)=RISK1 TIMEX;
        TIMEX=RISK1*(LOG(SURVTIME)-LOG(average followup time));
          * someone also uses simple forms: TIMEX=RISK1*LOG(SURVTIME);
          * or even: TIMEX=RISK1*SURVTIME; (not good enough); 
     PROPORTIONALITY_TEST: TIMEX;
RUN;

• Possibly, the easiest and powerful approach after SAS 9.2 is to use ASSESS statement, for example:

ODS GRAPHICS ON;

PROC PHREG DATA=ONE;

MODEL SURVTIME*EVENT(0)=RISK1;
     ASSESS PH/resample;
RUN;

ODS GRAPHICS OFF;

 

What’s New of PROC PHREG of SAS 9.2 (pdf)

 

American Medical Association declared obesity a “disease.”

American Medical Association declared obesity a “disease.”

"RESOLVED, That our American Medical Association recognize obesity as a disease state with 24 multiple pathophysiological aspects requiring a range of interventions to advance obesity 25 treatment and prevention. (New HOD Policy - Resolution 420)" - 06/16/2013

• New York Times (2013). A.M.A. Recognizes Obesity as a Disease
• Time.com (2013). The Best Cure for Obesity? Personal Responsibility.
• Boston.com (2013). Has obesity been mislabeled as a disease? Why doctors don’t mind.
• Bays (2013). Obesity, adiposity, and dyslipidemia: A consensus statement from the National Lipid Association.

Risk prediction and model comparison

 Risk prediction and model comparison
 
The potential approaches of prediction and comparison:

• Relative risk/hazard ratio/odds ratio, P-value.
• Sensitivity/specificity
• Area under ROC (receiver operating characteristics) curve (AUC)/Harrell's c statistic
• Somers' D (Kendall's Tau): the mathmatic conversion of Somers'D and c statistic are: [c statistic = D/2+0.5] or [D = (c - 0.5) x 2]. (SAS: PROC FREQ)
• NRI (net reclassification improvement)
• IDI (integrated discrimination improvement).
• K-fold cross-validation - Wikipedia
• ...

References:

• Pencina (2011). Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers (Comment).
• Pencina (2013). Understanding increments in model performance metrics.
• Pencina (2008). Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond.
• Measuring the Accuracy of Prediction Models - An International Symposium (2008): IDI, NRI and different c statistics (pdf)
• Hilden (2013). A note on the evaluation of novel biomarkers: do not rely on integrated discrimination improvement and net reclassification index.
• Liu (2012). Evaluating a New Risk Marker’s Predictive Contribution in Survival
• Mühlenbruch (2013). Assessing improvement in disease prediction using net reclassification improvement: impact of risk cut-offs and number of risk categories (Commentary).
• Cassell (2007). Don't be loopy: re-Sampling and simulation the SAS way (pdf).
• Kerr (2011). Evaluating the incremental value of new biomarkers with integrated discrimination improvement.

Software:

• Pepe Lab has some homemade software for biomarker/risk evaluation using Stata, SAS, R, SPSS, and even FORTRAN.
• Stata: to install 'Risk Prediction Package' (predcurve and incrisk), in a Stata session type: ".net from http://labs.fhcrc.org/pepe/stata/" and follow the instruction.To update the risk_prediction package at a later time, in Stata type: ".adoupdate risk_prediction, update".
• UCR posted SAS, Stata, and R codes for NRI & IDI on the website.
• Stata: How can I get a Somers' D after logistic regression in Stata?

 

rule of halves of diabetes

Rule of halves of diabetes
Source: DAWNStudy Diabetic Attitudes Wishes and Needs

Multicollinearity Issue

Multicollinearity Issue

Multicollinearity happens when two or more predictor/independent variables/regressors are highly correlated. I have been discussed about this issue many times by colleagues and journal reviewers. Paul Allison has a blog of some rules of thumb: When Can You Safely Ignore Multicollinearity? Wikipedia also has a article about this issue. It's true this is issue theoretically, but based on my experience in public health of chronic diseases, if the selection of predictors based on the logic/knowledge behind the model but not dump everything in one model, this should not be an issue.

Do We Really Need Zero-Inflated Models?

Do We Really Need Zero-Inflated Models?
Source: Statistical Horizon blog by Paul Allison
 
"... Of course, there are certainly situations where a zero-inflated model makes sense from the point of view of theory or common sense. For example, if the dependent variable is number of children ever born to a sample of 50-year-old women, it is reasonable to suppose that some women are biologically sterile. For these women, no variation on the predictor variables (whatever they might be) could change the expected number of children.

So next time you’re thinking about fitting a zero-inflated regression model, first consider whether a conventional negative binomial model might be good enough. Having a lot of zeros doesn’t necessarily mean that you need a zero-inflated model."

Read full text here
 
This question has haunted me for a while, thank Dr. Allison answered this question in such a layman-kind way. I like his book "Survival Analysis Using SAS: A Practical Guide" much; I don't have his book "Logistic Regression Using SAS: Theory and Application". Hope this logistic regression related book is in the same style.

More Blog on Statistical Horizon Blog