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</o:shapelayout></xml><![endif]--></head><body lang=LT link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal>Dear Traminer users and experts,<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I wrote this question few weeks ago but no one answered. I will make it brief this time, so maybe I will get some response <span style='font-family:Wingdings'>J</span><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I am interested in transitions to adulthood. I have two groups one is called 30-year-olds and another one - 25-year-olds. For both of these groups I have a sequence of life situation statuses. For 30-year-olds the sequence is longer than for 25-year-olds.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I want find the typology these sequences (transitions to adulthood) and I also want to assign sequences of 25-year-olds and 30-year-olds to these types (trajectories).<o:p></o:p></p><p class=MsoNormal>So the main issue for me is how can I assign the 25-year-olds that have shorter sequences to the clusters that were found based on analyses that also would include 30-year-old group. <o:p></o:p></p><p class=MsoNormal>I came up with several strategies, but I am not sure which on is better, or maybe there is something else I can do but I don’t know.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoListParagraph style='text-indent:-18.0pt;mso-list:l0 level1 lfo1'><![if !supportLists]><span style='mso-list:Ignore'>1.<span style='font:7.0pt "Times New Roman"'> </span></span><![endif]>The first strategy is that I simply run optimal matching calculations for the full dataset (including the ones that have long sequences and shorter ones) and those that have shorter ones’ are already assigned to some cluster. <o:p></o:p></p><p class=MsoNormal>Q1. My first question to You is: does this seem like a valid strategy to assign 25-year-olds to the clusters that are actually created using also 30-year-olds? <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>2. The second strategy is that I first analyze only 30-year-olds, then I extract ideal types representing each cluster, then I include these ideal types into dataset of only 25-year-olds and I rerun Optimal matching analysis. Then based on the shortest distance from each ideal type sequence to each participants’ sequence I assign them to those clusters. Something similar was discussed by Martin, P., Schoon, I., Ross, A., Beyond Transitions: Applying Optimal Matching to Life Course Research <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Q2. Does this seem like a more valid strategy than the first one? <o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Q3. Perhaps You could provide another option on how to do such assigning?<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>I would really appreciate any help on any of these questions. <o:p></o:p></b></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Rimantas<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>