[Traminer-users] minimum standards for datasets used with TraMineR

[Shawn Boles]

Hi All:

Any suggestions as to how to determine the minimum dataset size and missingness characteristics to which TraMineR may be applied sensibly would be helpful. I looked for information in documentation but did not see anything that I could use as a heuristic.

I am using TraMineR to analyze 5 years of BMI observations, coded  as a four level ordinal categorical variable for 5046 elementary school children (grades k-5) .  Only 414 of these have 5 observations ( ~ 56% of the K, 1 students measured at time 1  who could have had been measured in years 1 to 5.) .  Here are have two related, if not well stated, questions:


  1.  Is it legitimate to focus only on complete cases since I  only have 5 data points and high cumulative natural attrition. Testing  the complete cases against all cases reveals no substantive difference in values of predictors. The analyses from complete cases are informative,  while including all cases , regardless of imputation choice, just makes things noisy. I tried admitting only sequences of 4 or 5 but  results were still noisy.


  1.  Is five  too short a sequence object to use with TraMineR,  given the imputation  patterns required by the full dataset, regardless of whether they are due  to planned missingness or MAR?


  1.  Below is the number of cases with from 1 to 5 observations.

              1       2        3     4      5
              1846 1287 869 630 414

TraMineR is a great tool. I want to make sure I am using it appropriately.

Thanks.

Shawn Boles, Ph.D.
Senior Research Associate
Oregon Research Institute
1776 Millrace Drive
Eugene, Oregon 97403-2536
USA
Phone (541) 484-2123 ext 2225
Fax: (541) 484-1108




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