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</o:shapelayout></xml><![endif]--></head><body lang=LT link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>Dear Matthias Studer,<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>Thank You for sharing Your thoughts about my issue. It gave me some ideas to think about, but I am still lost in choosing the right method. I will explain my research questions a bit more, and why I generally think, the approach I am using can be useful to me.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify;text-indent:64.8pt'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>Perhaps the most general goal of my study is to challenge the ideas laid out in the theory of “emerging adulthood” by Jeffrey Jensen Arnett. In this theory, it is stated that transitional events that lead to acquisition of adult roles are not that important anymore for a person to become an adult. Instead, modern adulthood is achieved through acquisition of individualistic character traits such as becoming responsible, self-sufficient and so on. It is also said, that a person becomes an adult at about 30 years of age and between the adolescence and early adulthood there is now a new period – “emerging adulthood” – that is described by delay of entry in adult roles, prolonged identity exploration, instability, feeling “in-between” and so on. Critics of this theory argue that this stage, which is described by this features, is not really a stage but a trajectory. <o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'> The first that I want to do that is to show that not all people delay entry into adult roles. Holistic trajectories I reveal so far, shows that rather well (so do delay, some not). Now I also want to show that these trajectories differ on these characteristics of emerging adulthood. I see some of these differences in 30-year-olds, but I also want to take a look how people, who tend to follow one path or the other (trajectory), are different on these characteristics whilst being 25 years of age. I believe the differences would be seen during that period as well. <o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'> Perhaps this question (how holistic trajectories are related to psychosocial indicators) is a bit vague, but on the other hand, I believe that this methodology serves it substantially better, then focusing on single events (e.g. how marriage affects change in some behavior) that was used in previous studies. Single events are almost always confounded with other events (e.g. those that have children will most likely be married), and sequence analysis using OM also provides the dimension of time spent in some status. <o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>So now, I was thinking about what You suggested. I also created a fictitious dataset to play with and see how OM algorithm works by creating distances when I use different options for those short distances. <o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>First I used sequences like this </span><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'>(I used “right = "DEL"” argument when defining sequences)</span><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>.<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>123334445556666<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>12333444<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>44555666<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'>Then I tried inserting some other status as You suggested and transformed first and second sequence into<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>000000012333444<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F497D'>000000044555666<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'>In both cases OM algorithm still penalized the short sequences for transformation quite similarly. If I treated the missing to the left as void, it considered substitution of each missing value as best way to align (as much as I was able to understand from cost matrix). If I inserted manually some value, distance was also similar. <o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'>However, in both cases I found that my clusters extracted very highly linked to the length of sequences. The largest cluster contained most of long sequences (30-year-olds) and the rest were the short sequences divided into smaller clusters.<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'>So I feel like I have hit the wall here. I am still considering option A from my previous letter (</span><span style='font-family:"Times New Roman",serif;color:#1F497D'>(A) to start with only 30-year-olds and then recalculate the similarity of 25-year-olds to some representative sequence), however even that seems to be to much „innovative“ and I might find it very hard to defend. <o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span style='font-family:"Times New Roman",serif;color:#1F497D'>So I think I will just do separate analysis for 30- and 25-year-olds </span><span style='font-family:Wingdings;color:#1F497D'>L</span><span style='font-family:"Times New Roman",serif;color:#1F497D'><o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span style='font-family:"Times New Roman",serif;color:#1F497D'>Thanks again for everyone that shared thoughts about this!<o:p></o:p></span></p><p class=MsoNormal style='text-align:justify'><span style='font-family:"Times New Roman",serif;color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><span style='font-family:"Times New Roman",serif;color:#1F497D'>Rimantas</span><span lang=EN-US style='font-family:"Times New Roman",serif;color:#1F4E79'><o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='color:#1F497D'><o:p> </o:p></span></p><div><div style='border:none;border-top:solid #E1E1E1 1.0pt;padding:3.0pt 0cm 0cm 0cm'><p class=MsoNormal><b><span lang=EN-US style='mso-fareast-language:LT'>From:</span></b><span lang=EN-US style='mso-fareast-language:LT'> traminer-users-bounces@lists.r-forge.r-project.org [mailto:traminer-users-bounces@lists.r-forge.r-project.org] <b>On Behalf Of </b>Matthias Studer<br><b>Sent:</b> Tuesday, February 17, 2015 12:44 AM<br><b>To:</b> Users questions<br><b>Subject:</b> Re: [Traminer-users] linking short sequences with custers based on long sequences<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'>Dear Rimantas Vosylis,<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'>Here are my thought about your issue. You are studying an outcome of the trajectories, whereas sequence analysis is often used to study how starting condition influence the following trajectories. This makes big differences.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'>I think you should develop the exact assumption you are making. Why do you think that there is a relationship between trajectories and psychosocial indicators exactly (please find some example below)?<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoListParagraph style='margin-left:53.25pt;text-indent:-18.0pt;mso-list:l0 level1 lfo2'><![if !supportLists]><span lang=EN-US style='color:#1F497D'><span style='mso-list:Ignore'>-<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='color:#1F497D'>Previous semester influence current psychosocial indicator. In this case, you could align the sequence to the end of observation and add the state “in school/education” for unobserved semester (at the beginning of the sequence). You’ll have complete trajectories in both cases. Depending on the issue, this may be a good solution. Concretely, this would lead to recode trajectory:<o:p></o:p></span></p><p class=MsoListParagraph style='margin-left:125.25pt;text-indent:-18.0pt;mso-list:l0 level3 lfo2'><![if !supportLists]><span style='font-family:Wingdings;color:#1F497D'><span style='mso-list:Ignore'>§<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span style='color:#1F497D'>22333445777788<o:p></o:p></span></p><p class=MsoListParagraph style='margin-left:89.25pt;text-indent:-18.0pt;mso-list:l0 level2 lfo2'><![if !supportLists]><span lang=EN-US style='font-family:"Courier New";color:#1F497D'><span style='mso-list:Ignore'>o<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='color:#1F497D'>To <o:p></o:p></span></p><p class=MsoListParagraph style='margin-left:125.25pt;text-indent:-18.0pt;mso-list:l0 level3 lfo2'><![if !supportLists]><span style='font-family:Wingdings;color:#1F497D'><span style='mso-list:Ignore'>§<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span style='color:#1F497D'>111111111122333445777788<o:p></o:p></span></p><p class=MsoListParagraph style='margin-left:89.25pt;text-indent:-18.0pt;mso-list:l0 level2 lfo2'><![if !supportLists]><span lang=EN-US style='font-family:"Courier New";color:#1F497D'><span style='mso-list:Ignore'>o<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='color:#1F497D'>Where state 1 is being in school<o:p></o:p></span></p><p class=MsoListParagraph style='margin-left:89.25pt;text-indent:-18.0pt;mso-list:l0 level2 lfo2'><![if !supportLists]><span lang=EN-US style='font-family:"Courier New";color:#1F497D'><span style='mso-list:Ignore'>o<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='color:#1F497D'>Your sequence would describe the last 24 semesters in all cases.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoListParagraph style='margin-left:53.25pt;text-indent:-18.0pt;mso-list:l0 level1 lfo2'><![if !supportLists]><span lang=EN-US style='color:#1F497D'><span style='mso-list:Ignore'>-<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='color:#1F497D'>How are whole trajectories and psychosocial indicators linked from an holistic perspective? These kind of research questions are generally too vague for me. The research question assume that you measure complete trajectories, hence, you need predicting the end of incomplete trajectories. In order to render the uncertainty of the predictions, I use multiple imputation in some ways (but I never tried). I know Brendan Halpin has written an article about that. Strategy A goes in the same direction but do not render the uncertainty of the predictions.<o:p></o:p></span></p><p class=MsoListParagraph><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoListParagraph style='margin-left:53.25pt;text-indent:-18.0pt;mso-list:l0 level1 lfo2'><![if !supportLists]><span lang=EN-US style='color:#1F497D'><span style='mso-list:Ignore'>-<span style='font:7.0pt "Times New Roman"'> </span></span></span><![endif]><span lang=EN-US style='color:#1F497D'>I think strategy B may be meaningful because it may render the differences (in life history) between having 25 or 30 years old. However, you should be more precise about your assumption.<o:p></o:p></span></p><p class=MsoListParagraph><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'>Because I can only think about the relation you are studying (trajectories and psychosocial indicators) using the first research question, I would use that method. If you were studying the results of starting conditions (the effect of the situation at the end of education) I would go toward multiple imputation.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'>Hope this helps.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='color:#1F497D'>Matthias<o:p></o:p></span></p><p class=MsoNormal><span lang=FR-CH style='color:#1F497D'><o:p> </o:p></span></p></div></body></html>