BIOS601 AGENDA: Thursday September 10, 2015

Agenda for Thursday Sept 10, 2015

• Discussion of issues in the Assignment on measurement
   
  Q1 and Q2 (measuring 'Readability'): answers need not be handed in; just think about the issues; If there is time, we might discuss and do some 'measuring' in class.
  
  Q3, Q4, Q5, Q6, Q7, Q14: Answers to be handed in.
  
  Q8, Q9, Q10, Q11, Q12, Q13: answers need not be handed in. If there's time, you and we will think about what the answers to them might have looked like.
  
  Remarks: this topic of measurement is probably new for you, as it was for JH when he began in cancer clinical trials in 1973, and oncologists (cancer doctors) were judging responses of advanced cancer to chemotherapy by measuring tumours by 'palpation'.
  
  Just because (random) measurement errors tend to cancel out in averages doesn't mean that errors in measurement can be ignored. For example, how comfortable would you be in measuring how much physical activity JH does by having him wear a 'step-counter' for a randomly selected week of the year, and using that 1-week measurement as an 'x' in a multiple or logistic or Cox regression? See slides 7 and 8 from part of JH's "Scientific reasoning, statistical thinking, measurement issues, and use of graphics: examples from research on children" at Royal Children's Hospital in Melbourne, earlier this year. pdf
  
  Some of the the terminology will be new to you, and so (as you will discover if you do run the simulations in Q8 -- you are encouraged to do so -- of how well you can estimate the conversion factors between degrees F and degrees C) will some of the consequences of measurement error. The "animation (in R) of effects of errors in X on slope of Y on X" might be of interest, as might the java applet accompanying "Random measurement error and regression dilution bias". These consequences are rarely touched on, yet alone emphasized, in theoretical courses on regression, where all 'x' values are assumed to be measured without error! Welcome to the REAL world.
  
  For this exercise, and the topics it addresses, the most relevant portions of the 'surveys' resources are Measurement: Reliability and Validity and Effects of Measurement Error
  
  Computing issues that may arise in Q14: Dates are a pain, even in R. If you get stuck, use some of the R code supplied, to compute week and day of week. Incidentally, whereas the exercise makes reference to 104 weeks, there are a few weeks with some missing data, so best keep them out of the calculations for now (in practice JH would try to use all the data, but the imbalanced data have a messier EMS structure that -- for now -- distracts us from the main point).