```Date: Sun, 25 Sep 2011 20:32:15 -0400 Reply-To: R B Sender: "SPSSX(r) Discussion" From: R B Subject: Re: 2 x (2) design with binary-->continuous within-subject variable Comments: To: ac11ca In-Reply-To: <1316920405699-4837785.post@n5.nabble.com> Content-Type: text/plain; charset=ISO-8859-1 You need to better describe the administration of the experiment. It looks like you have four measurements for each subject, two of which are binary and two are bounded between 0 and 100. Is that correct? Please provide a concrete example of how this experiment was administered to a single subject. A step-by-step explanation would be helpful (i.e., subject is presented with x and responded with x, then subject is presented with x and responded with x, etc.). It isn't clear to me, for instance, how the first subject in your dataset illustration obtained a value of 0.15 (second case in your dataset). Ryan On Sat, Sep 24, 2011 at 11:13 PM, ac11ca wrote: > Hi there, > > I am hoping that you might be able to help me analyse some data from a > decision-making experiment I ran recently. > > I have a 2 x (2) design where the within-subjects measure variable changes > from a binary response (i.e., 0,1) to a continuous response (i.e., 0-100). I > realise that this is very odd, but it is central to my current research > question: Are people more like to prefer a risky gamble over a safe gamble > if > the choice is presented as a single play or the accumalted sum of 100 plays? > > My data looks like this in SPSS (Note: Format = between-subjects > categorical > IV [coded 1,2] and Plays = within-subjects categorial IV [coded 1,2], and > Choice = DV that is half the time binary [0,1] and half the time > continuous[0-100]): > > ID Format Plays Choice > 1 1 1 0.00 > 1 1 2 0.15 > 1 2 1 1.00 > 1 2 2 0.78 > . > . > . > . > 93 1 1 0.00 > 93 1 2 0.01 > 93 2 1 1.00 > 93 2 2 0.97 > > I started by analysing my data with a mixed ANOVA and found an interaction, > which is what I was hypothesising. Of course, one of the assumptions of the > ANOVA is that the data are normally distributed, which they clearly are not > with my binary response data. > > To get around this problem I conducted a repeated measures logistical > regression using the SPSS Generalised Estimating Equations function (GEE) > under a binary model type. However, the GEE method accepts only one > distribution for my within-subjects variable: binomial or scale responses. > If > I chose scale, then I am just running an ANOVA (I think!). If chose > binomial, > then I have to convert the continuous DV to a binary DV (and cut all 50/50 > responses), which basically undermines the motivation of the experiment and > eliminates crucial differences. > > Thus, I think that I must use the original mixed ANOVA analysis and produce > some hand-waving sort of justifcation. I was wondering if anyone might be > able to help me with this justification. For example, what is the impact of > having a binary DV in the middle of a mixed ANOVA and is it really so bad? > > Thanks for any help that you might be able to provide. If anyone wants to > see > the data, feel free to email me at ac11ca[at]hotmail[dot]com. > > Cheers, > Adrian > > > -- > View this message in context: http://spssx-discussion.1045642.n5.nabble.com/2-x-2-design-with-binary-continuous-within-subject-variable-tp4837785p4837785.html > Sent from the SPSSX Discussion mailing list archive at Nabble.com. > > ===================== > To manage your subscription to SPSSX-L, send a message to > LISTSERV@LISTSERV.UGA.EDU (not to SPSSX-L), with no body text except the > command. To leave the list, send the command > SIGNOFF SPSSX-L > For a list of commands to manage subscriptions, send the command > INFO REFCARD > ===================== To manage your subscription to SPSSX-L, send a message to LISTSERV@LISTSERV.UGA.EDU (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD ```

Back to: Top of message | Previous page | Main SPSSX-L page