2012 April 13 Frank, Warren, JoAnn

  • It's a good idea to write up the propensity model for graft type in primary ACL reconstruction for publication in an orthopedic journal.
  • JoAnn to write up methods and results from propensity model.
  • Take surgeon out of the propensity model and look at the change in the other variables.
  • For SF36 paper: Frank thinks we should include some of the internal model validation results in the manuscript, maybe in an online supplement. Include R^2 and Dxy. Increase bootstrap reps to 300.
  • The mental and physical component score models have good validation results. Some of the other models have a bit of a drop. However, the other models also had better R^2 and Dxy to begin with.
  • Frank is surprised by a lower signal to noise ratio than he expected in these models.
  • Frank is concerned that the validate and calibrate functions might have a bug for proportional odds models. Try re-fitting one of the models with (1) the baseline version of the outcome only and (2) a model with about 20 degrees of freedom selected from clinical knowledge rather than the p values from the full models. Then run the validate and calibrate functions on the new models and compare.
  • For the mental and physical component scores, there are hundreds of unique values of the outcome. Try rounding the outcome to the nearest whole number. If there are at least 100 unique values, re-run. This will help things run faster.

2012 March 5 Frank, Warren, JoAnn

  • We looked at the QALY output (descriptives.pdf). Frank likes the spaghetti plots and the lowess smoothed curve with grayed data. He noted that if we do any modeling with this measurement, we need to include all patients. (We are currently only calculating this for those with values of sf6d at both t2 and t6).
  • Frank recommends that we present the QALY in the paper using a function of his in Hmisc called curveRep. It finds representative curves. In this case, he recommends using 4 or 5 equally-spaced points.
  • We discussed how to present the multitude of output we have on the 8 sf36 domains. Frank suggested we have a plot similar to plot(anova(mod)), but for each explanatory variable in the model, we have a point plotted for each of the 8 outcomes, plus for the 2 summary component scores (mcs and pcs), with each outcome represented by a different plotting character. The quantity plotted is the chi-square statistic minus the degrees of freedom. This plot would require a little programming. Frank wants me to send him the code after I do it.
  • Could put all the nomograms in an online supplement.

2011 December 5 Frank, Warren, JoAnn

  • We're planning on submitting one paper on sf36 alone, and one paper on koos, ikdc, and marx together. Frank recommends we try to use the same type of model for all the outcomes in one paper.
  • Think about using prop odds for all these models. Check prop odds assumption for: sf36, koos, ikdc, and marx by plotting partial residuals. The prop odds model makes far fewer assumptions than the normal model. Prop odds assumes that the logit of the cdf of Y for separate factors are parallel.
  • Can also consider quantile regression. It only assumes continuity of the outcome, and makes no other distributional assumptions about the outcome. It allows you to estimate the median (or any percentile). This estimate has less precision than a mean estimate (in the case of normality).
  • We will use the raw IKDC score rather than the normalized one.
  • Compare the following: ols with cluster adjustment using cluster bootstrap (uses +- 1.96, which is making the assumption that the beta hats are nomally distributed), using Gls and specifying a covariance structure to handle clustering, and using ols or Gls with bootcov, but using the bootstrap estimated confidence intervals, which use a nonparametric percentile method. This doesn't assume normality of the beta hats. You can plot a histogram of the bootstrap estimates to help assess normality of the bootstrap beta estimates
  • Is adjusting for surgeon masking the effect of graft type? Remove surgeon from the propensity model and re-run everything. Add the results to the plot of the confidence intervals.
  • In the koos or past marx model, make two nomograms: one with ols and one with lrm, and see if they are similar
  • Want to look at utility for general health outcomes. Calculate and plot the means of SF6D over time. Compute QALY as the area under the curve below the SF6D over time for each patient. (For now, only calculate these for those patients with both 2 year and 6 year follow up.)

2011 September 12 Frank, Warren, JoAnn

  • Remove propensity score from both sets of models and look at the effect on the estimate and CI for graft type. If it is still not significant, we will exclude propensity score.
  • Look at the shape of the propensity of allograft for all models
  • Look at the partial effects of the propensity model to see if there is one main driver of the propensity score

  • Change caucasian to white in create, mixed, and koosmodels.
  • Try adding Key() with no arguments after the plot of the interactions to get labels.

  • Frank wants to see more residual plots of the koos models. Says the one for the symptoms score is okay. Do the plots on the handout for the Gls case study. He will use these to decide whether to stick with the Gls model for the other 4 koos outcomes or try a transformation or a proportional odds model (or something else?).

  • Frank says our correlation estimate from the koos symptom score model is very low. However, the correlation from the pain score is higher. One way we could verify this is to make a scatterplot of a particular outcome at t2 by the corresponding outcome at t6, Frank says we should discuss the correlation in the paper.

  • Make one variable with all meniscus treatment options (separately for lateral and medial) so that the comparisons being made make sense. Replace the mm.excat, lm.excat, noTxTear and repair variables with this variable in the koos and sf36 models.
  • After that is done, if we still have effect directions that don't make sense, we could look at how well all the other predictors predict the amount of meniscus excised.

  • See if the effect of the baseline covariates is different for different follow up times by adding an interaction term for (unsplined) time with all the other baseline covariates. Look at the test for all interactions with time.

2011 August 26

  • Present: Warren, Suzet, Emily, Laura, Thomas, JoAnn
  • Can we make a nomogram with these models?
  • JoAnn will draft paragraph for stat methods
  • Answer Warren's questions about model output.
    • Frank suggested removing the propensity score from the model to see if graft type is significant, and if it is not we can remove the propensity score from the model...
    • Plot effects of the lm.excat*lfc.chondcat interaction. (Check the different output of Frank's functions first.)
  • We will ask Frank for help with model interpretation
  • Fit models for IKDC and KOOS.

2011 August 8 Frank, Warren, JoAnn

  • Frank wants me to do some verifying of the ordinal program. Could check by subsetting to only 2 year outcomes, and check that lrm and ordinal give identical output. (This will not be billed to Sports Medicine.)
  • For the sf36 domain scores, we will probably go with lrm and then use robcov or bootcov (since the ordinal package takes a long time to run and doesn't converge). JoAnn will try both robcov and bootcovon several models and compare the output. One way to compare them is by taking the ratio of diag(vcov(fit)) for each model fit.
  • We will use areg impute to impute any remaining missings.
  • We reviewed the current missings for these models after I had already subsetted out rows with no follow up. They are much lower, but several remain for age. Zhouwen and Suzet are checking on them.
  • Frank noted a clustering in the physical function outcome. We think this is due to a ceiling effect in the likert-type items in this section.

2011 July 29

  • Present: Warren, Laura, Suzet, Emily, Zhouwen, JoAnn
  • Discussed "missing" records that were not used in the sf36 model, and whether these were missing because the person didn't have follow up for that time point.
  • JoAnn will verify that everyone in the analysis data has at least one followup.
  • In the descriptives document, JoAnn will show descriptives of only those who have t2 follow up or t6 follow up for the variables that are shown by time point, to help determine how many missing values.
  • JoAnn will add to code that makes the previous surgery graft type variables that if a patient had aclrep ONLY (not intacl or extacl) on a particular knee, that they will have "non applicable" recorded for the previous surgery graft type for that knee, ignoring the allo or auto marked for that knee.
  • JoAnn will add competition level and sport to the outcome models.
  • Zhouwen and Suzet are going to check on missing values for age.
  • To investigate the surgeon initials "ERR," JoAnn will check the year, time point, and regn for those records.
  • JoAnn will add multiple imputation, probably with areg.impute
  • JoAnn will add descriptives of all the individual items and summary scores of the koos, IKDC, sf36, sf6d, and marx.
  • JoAnn will run a redundancy analysis on these measures.

2011 July 18 Frank, Warren, JoAnn, R

  • Talked about the normalization of the SF36. Frank is not a fan of normalizations in general.
    • JoAnn will plot the raw scores by the normalized ones for a specific domain to see if it is a linear transformation.
  • Decided to model the eight domain scores instead of the component scores. Can use a proportional odds model and adjust afterward using robcov OR use ordinal regression with a random effect via the ordinal package in R. The mixed effects can handle missing not at random better. (?)
    • JoAnn will run both types of models on the physical function domain.
  • Need to compare those with T2 only vs. those with T2 and T6 based on the outcomes.
  • Discussion about time-dependent covariates. They make inference and interpretation difficult. Frank is worried about including marx activity level as a time-dependent covariate. We will limit marx to baseline only.
    • Will try to set up a clinic that Jonathan can attend to discuss this.

2011 May 2 JoAnn, Warren, Frank

  • Looked at results from fastbw function we ran to decide which subscores to model. We could just decide to run the summary scores since we saw that R squared = 1.
  • Frank approved of our plan for controlling for excision and knee variables. (lm.ex*(lfc + ltp) + mm.ex*(mfc + mtp)) He also is good with our lumping plan.

2011 Mar 18 JoAnn and Warren

  • Current priority is finalizing the sf36 models.
  • JoAnn will add more demographics to the descriptives.
  • Decided we will treat mental and physical composite scores and utility score as continuous, and give only graphs for the 8 domain scores. Analysis plan updated.
  • Will bring up with Frank the sparse combinations of surgeons and allografts.
  • A large number of allograft propensity scores are missing due to missing values of aclrep.rt. This uncovers a bigger issue of whether we think allografts are predicted by previous surgery on other knee, previous surgery on same knee and also a big recoding job. JoAnn will look at ptg.auto and ptg.allo and figure out whether there are enough observations to consider whether a previous autograph came from the patella or hamstring.
  • Once given the green light, JoAnn will work on combining the 2002, 2003, and 2007+ data for an allograft propensity model paper.
  • Data issues
    • There is a large number of missing in the occupation variables that should be 0. JoAnn confirmed that this is for year 2002. JoAnn emailed Thomas and Zhouwen.

2011 Mar 04

1) Emily has data dictionary questions for Thomas

2) Thomas was able to fix the problems Suzete gave to him

3) Post code ~ Country name

2011 Feb 25

1) Waiting for Thomas to finish his thing, and then Zhouwen will do the merge

2) Thomas:

-data has always had spaces, he should be able to fix the variables that have problems w/levels

-Suzete & Emily will do their stuff, give to Thomas, who will give to Zhouwen

-re-merge early next week ('02-'03)

3) Jo Ann:

-will not be able to fix her problems until the merge happens

-surgeon experience

2011 Feb 11

1) Suzete:

-checked dates on questionnaire, they should all be correct

-fixed the variables that were empty in the merge & (that couldn't be merged), therefore that's why they were blank

-she will let Thomas, Zhouwen and Jo Ann know when she deposits, and they can re-merge

-she is working on the zip codes

-she needs to enter surgeon forms

2) Thomas: Downloaded info from the Census (FDP) site; we now have a complete copy of all the 2009 SHAPE data

3) Jo Ann:

-Looking at smoking at each time point, they asked something different at one poitn, Dr. Dunn's recoded it b/c he didn't like the way it was worded

-3 people are n/a & 2 people are both...we could probably exclude the "both" but don't know what's up with the n/a. (If Jo Ann sends Emily info, se can figure out who the 5 people are, and remove/fix them)

4) We will use sport; the participants' sport we use will be their primary sport and competition level (sport1ik)

5) Can we get insurance type from persons' questionnaires? Payor type? This could be problematic b/c a lot of sites will only keep the most up-to-date info

2011 Feb 04

1) Jo Ann: Updated what we talked about last time, and made a report of the "wonky" dates, and put it in an error output file for Suzete

2) Suzete: Is looking into the ones missing from the surgeon forms ('02 and '03), she found four from '03 (3 RDP, 1 ECM), she is going back to the source file to see if they're there

3)Zhouwen: Re-did the multi-year merge

4) Suzete and Emily will check the T-6 follow-up variables and see if they are populated. T-6 should be 1's, all others should be 0's. There are blanks that shouldn't be there, Thomas and Suzete will look into this.

2011 Jan 28

1) Jo Ann :

-working on reshaping the longitudinal data (SF 36 Outcomes)

-discussion of Longitudinal model for SF36, and Outcomes in the ACL Study

-To Do: will post the updated before the reshape; if she sees any outliers that don’t make sense, she will send the info to Suzete, who can look into it and correct it.

2) Suzete and Emily will be able to go through and connect/get rid of/check the dates

3) Fist plan of attack is to look Zhouwen’s mapping program and find the imputed variable

4) Thomas will try to make it so Dr. Dunn can PDF things in the Latek Program

5) Zhouwen:

-completed mapping and a bit of scoring, he is trying to figure out the programs and how the locater works

-He suspects we are approximately two months away from incorporating GIS data in analyses

6) Emily will send Zhouwen the County information

7) Thomas:

-updated the index checker, rebuilt it, and now it is outputting everything Suzete wants and not anything she doesn’t want

8) We need to add some sort of variable that indicates whether or not we have checked something

9) Suzete has been checking the error output

2011 Jan 14

1) Emily:

-figured out where the 20 extra records came from

-wants to be able to see previous versions each time, that way she can correct/compare with the newer versions

-she will send the list of variables to Joann and Dr. Dunn for them to create a code

2) Suzete is working on '04 data

3) Zhouwen created a comprehensive file

-There are currently 3 files: 1) Super 2) Public 3) Private

4) Thomas has the names to work in the index checker

2011 Jan 01

1) Emily:

-will give Zhouwen 3 CD's of data about the Morgan Project

-will check on changes in data (10 new patients)

2) We are missing 2 variables with PT4, Suzete will add variables and Thomas will redo the output

3) Zhouwen:

- noticed changes on '02 data, he will double check and see what's going on

- will create a comprehensive file and a multi-year for '02 & '03

4) Once we get all of the barcodes fixed, they should be unique to each patient and to each surgery

5) Joann:

-needs access to tracker (should have it soon)

- working on '05 data & correcting errors

6) Dr. Dunn will start working on the SF36, & Joann will go in and make a draft of it

2010 Dec 17

1) Zhouwen will complete the re-merge of ‘02/’03 on Monday 12-20

2) 2004/05 was missing some patient info, but the surgeon was there

3) Zhouwen needs the barcode for ’02 data
  1. Suzete will get it for him, but we will still need to add things because the barcode was T6
4) On ’03 data, under consent: only one person is missing consent status

5) Virtual Machine
  1. Thomas will re-install teleform on this, which will push it into the file share server, then we will have to migrate the stuff over….and can then do a test run

2010 Dec 10

1) Discussion of encryption rules and regulations

2) Zhouwen: will run a test merge on 2005 & Thomas will run the indexor (error report)

3) Jo Ann will start tackling the '05 cleaning

4) Status of '02/'03 Stuff

-Zhouwen is working on it

-a couple consent files are missing for '03 patients...Zhouwen will send to Emily and she will help fix

2010 Dec 03

1) Thomas discussed the teleform file server problem (he should be able to fix this)

-Mike Maday said there may be corrupt registry files on the teleform fs; we need to follow up with him re: domain group

2) Suzete is working on 2004

-There are many cases where the patient questionnaire is missing (n/a)

-She checked the sources files looking for surgeons, found them in the final merge, but they are not supposed to be in there (she and Zhouwen will look into this)

3) Zhouwen is trying to figure out what is going on with the follow-up variables ('02-'03)

-He will compare them with Suzete's work

-There was a larger discussion on this subject.... maybe Zhouwen or Suzete could elaborate??

4) Suzete asked if Zhouwen can ad in the PHI for '02 & '03

5) Data file discussion (private/public)

2010 Nov 19

1)Cleveland Clinic Study (Socioeconomic Study)
  1. PI: Morgan Jones
  2. Computer ordered by Zhouwen
  3. We will keep this “on our radar”
2)Still some small quirks about the 2003 data
  1. All of the new variables merged in perfectly…all of the variables that had older counter-parts did not
  2. Suzete will purge some old variables in the t2 source file
3)Orbits/On-Site Study
  1. Kurt has a paper he wants written that will mostly include onsite data (for late December/early January); Emily and JoAnn can work in the analysis in the weeks to come
4)2002-2003: How to solve having duplicate quirky variables….Discussion of follow-up variables
  1. Use “follow up” for T2 and T6
  2. Suzete will go through source files and update
  3. Same variable, different variable names….can we merge them?
  • “lclrep” does not exist in Ipak; “oplcl” does not exist in questionnaire….we need to merge these two
  • Zhouwen did this in ’02, we need to do it in ’03…but there is no “lclrep” in ‘03
  • Zhouwen and Suzete will look into this

2010 Nov 12

Foswiki Instructional Meeting
  • Free & Open Source Wiki
  • biostat.mc.vanderbilt.edu
  • To register, go to the main page and use your First and Last name; No space in-between and capitalize the first letter of each
  • It may be more efficient to edit the Wiki itself instead of uploading file attachments
  • We need to think about our formatting; what links should we make?
  • It would be great to have something that could track what we are doing; if we want to make a change or ask questions, it could notify everyone; we could respond and it would show who has worked on it, etc. therefore eliminating extra work
  • We need to set up notifications (do this through your own wiki page)
  • It would be nice if we could have a Nomogram link on the page
Topic revision: r24 - 27 Nov 2017, DalePlummer

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