PhD-delay Dataset for Online Stats Training

<p>This is a dataset&nbsp;used for the online stats training website (<a href="https://www.rensvandeschoot.com/tutorials/">https://www.rensvandeschoot.com/tutorials/</a>) and is based on the data used by&nbsp;&nbsp;<a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0068839">Van de Schoot, Yerkes, Mouw and Sonneveld 2013</a></p> <p>&nbsp;</p> <p>Among many other questions, the researchers asked the Ph.D.&nbsp;recipients how long it took them to finish their Ph.D.&nbsp;thesis (n=333). It appeared that Ph.D.&nbsp;recipients took an average of 59.8 months (five years and four months) to complete their Ph.D.&nbsp;trajectory. The variable B3_difference_extra measures the difference between planned and actual project time in months (mean=9.97, minimum=-31, maximum=91, sd=14.43).&nbsp;For the the exercises we are interested in the question whether age (M = 31.7, SD = 6.86) of the Ph.D.&nbsp;recipients is related to a delay in their project.&nbsp;The relation between completion time and age is expected to be non-linear. This might be due to that at a certain point in your life (i.e., mid thirties), family life takes up more of your time than when you are in your twenties or when you are older.&nbsp;So, in our model the&nbsp;gapgap&nbsp;(<em>B3_difference_extra</em>) is the dependent variable and&nbsp;ageage&nbsp;(<em>E22_Age</em>) and&nbsp;age2age2(<em>E22_Age_Squared&nbsp;</em>) are the predictors.</p> <p>For more information on the sample, instruments, methodology and research context we refer the interested reader to &nbsp;<a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0068839">Van de Schoot, Yerkes, Mouw and Sonneveld 2013</a>.</p> <p>&nbsp;</p>