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> On 17 Oct 2014, at 06:33, Lisa Newson <[log in to unmask]> wrote:
>
> I have made numerous attempts to unsubscribe from this list. None of the instructions appear to work.
> Please could I be removed.
> Kindest regards
> Lisa
>
> Sent from my iPhone
>
>> On 17 Oct 2014, at 00:09, PSYCH-POSTGRADS automatic digest system <[log in to unmask]> wrote:
>>
>> There are 3 messages totaling 378 lines in this issue.
>>
>> Topics of the day:
>>
>> 1. Paid Research Assistant Post - University of Chichester
>> 2. Multinomial Logistic Regression (2)
>>
>> ----------------------------------------------------------------------
>>
>> Date: Thu, 16 Oct 2014 12:12:56 +0000
>> From: Antonina Pereira <[log in to unmask]>
>> Subject: Paid Research Assistant Post - University of Chichester
>>
>> We are currently seeking a Research Assistant to join the Psychology and Counselling Department. The post-holder will be responsible for the identification and recruiting of young and older adult participants for a study exploring the potential of an innovative Prospective Memory measure as a specific and sensitive tool to discriminate healthy and cognitively impaired adults.
>>
>>
>> You will conduct experimental sessions which will consist of a series of standardized psychometric tests, health and well-being questionnaires and computer-based lexical decision tasks involving Prospective Memory activities. You will also be responsible for the performance, integrity and security of the respective database of psychometric testing protocols.
>>
>>
>>
>> Qualified to at least degree level you will work as a proactive member of a project team and will undertake literature searches and reviews; data collection and analysis and contribute to the production of research outcomes. You will demonstrate excellent interpersonal and organisational skills and have experience in psychometric testing.
>>
>>
>>
>> Informal enquiries about the recruitment process are welcomed by Dr Antonina Pereira on 01243 816359 or email - [log in to unmask]<mailto:[log in to unmask]>?
>>
>>
>>
>> · Closing Date: 30 October 2014
>>
>> · Interview Date: TBC
>>
>>
>>
>>
>>
>> For full details of the post, please visit our website https://unchili.webitrent.com/unchili_web/wrd/run/ETREC105GF.open?WVID=4211941WJu
>>
>>
>> or email: [log in to unmask]<mailto:[log in to unmask]>.
>>
>>
>>
>>
>> Best Wishes,
>>
>>
>>
>> Antonina
>>
>>
>>
>> This e-mail and any attachments are intended for the addressee only and may be confidential. If you are not the intended recipient, please advise the sender as soon as practicable and delete the e-mail from the system. The University of Chichester is a company limited by guarantee, registered in England and Wales. Registration number 4740553. The registered office is College Lane, Chichester, West Sussex, PO19 6PE.
>>
>> ------------------------------
>>
>> Date: Thu, 16 Oct 2014 08:43:16 -0700
>> From: Jeremy Miles <[log in to unmask]>
>> Subject: Re: Multinomial Logistic Regression
>>
>> When you add more predictors, you control for those other predictors. If
>> that's what you want to do, that's what you should do. (That is interfering
>> with the model, because it changes the model - but that might be the model
>> you want).
>>
>> You can still look at interactions if you want to.
>>
>> I'm not sure what it's saying about model fit, 'cos I don't use SPSS . But
>> I would have thought you wanted significant model fit.
>>
>> Also, why aren't you doing ordinal logistic regression? Your outcome looks
>> ordinal, rather than categorical to me.
>>
>> There's a nice book on all this by J Scott Long called "Regression analysis
>> for categorical and limited dependent variables."
>>
>> You say "What I'm interested in mainly is does group
>> membership affect their yes/no answer". So is yes/no answer your outcome? I
>> assumed it was group membership. If it's yes/no, you only have two options,
>> and regular binary logistic regression will work.
>>
>> Jeremy
>>
>>
>>> On 15 October 2014 09:27, Helen Mann <[log in to unmask]> wrote:
>>>
>>> Hi,
>>>
>>> I have three groups low/medium/high and their yes/no answer to questions.
>>>
>>> If I do a multinomial logistic regression for each question and lump in
>>> other things such as "age", "gender" etc. does that interfere with my model
>>> (like it would if you added things in a normal linear regression?). As I
>>> have loads of IV's I thought I would lump them all into the one analysis to
>>> save time - thinking that as it's all to do with odds ratios that there
>>> would be no looking for interactions between the IV's on the DV (e.g. if
>>> group and gender was there it would look at group on answer and gender on
>>> answer but not affect of group and gender on answer)...I have found this
>>> from Strathclyde University (
>>> https://www.strath.ac.uk/aer/materials/5furtherquantitativeresearchdesignandanalysis/unit6/multinomiallogisticregression/) and
>>> have been trying to follow it but I think what is confusing me is this idea
>>> of model fit...what does it mean by model fit??? Why do I want the model
>>> likelihood ratio test to be *non significant.*
>>>
>>> What I'm interested in mainly is does group membership affect their yes/no
>>> answer - does it complicate things to add in other variables? If I had
>>> continuous data I would run an ANOVA but alas its categorical...
>>>
>>> Help!
>>> Helen
>>
>> ------------------------------
>>
>> Date: Thu, 16 Oct 2014 17:32:42 +0100
>> From: Tom Bailey <[log in to unmask]>
>> Subject: Re: Multinomial Logistic Regression
>>
>> Hi Helen
>>
>> As I understand your question then you might want to use binary logistic regression, with two dummy coded variables (medium vs low) and (high vs low) predicting your outcome variable of yes/no in block 2....following the control variables already entered in block 1. Although granted you would have to do a separate logistic regression for each question (could be problematic if you've got loads of questions). I don't often deal with data that is categorical but assuming you have quite a few questions, is this design not most suitable for a pearson chi-square test?
>>
>> Regards
>>
>> Tom
>>
>> Tom Bailey BSc MSc
>> PhD Researcher at The University of Nottingham
>>
>> Blog - http://tomjamesbailey.wordpress.com
>> LinkedIn - uk.linkedin.com/in/tomjbailey7
>> Twitter - https://twitter.com/TomJBailey7
>> ________________________________________
>> From: Research of postgraduate psychologists. [[log in to unmask]] On Behalf Of Jeremy Miles [[log in to unmask]]
>> Sent: 16 October 2014 16:43
>> To: [log in to unmask]
>> Subject: Re: Multinomial Logistic Regression
>>
>> When you add more predictors, you control for those other predictors. If that's what you want to do, that's what you should do. (That is interfering with the model, because it changes the model - but that might be the model you want).
>>
>> You can still look at interactions if you want to.
>>
>> I'm not sure what it's saying about model fit, 'cos I don't use SPSS . But I would have thought you wanted significant model fit.
>>
>> Also, why aren't you doing ordinal logistic regression? Your outcome looks ordinal, rather than categorical to me.
>>
>> There's a nice book on all this by J Scott Long called "Regression analysis for categorical and limited dependent variables."
>>
>> You say "What I'm interested in mainly is does group membership affect their yes/no answer". So is yes/no answer your outcome? I assumed it was group membership. If it's yes/no, you only have two options, and regular binary logistic regression will work.
>>
>> Jeremy
>>
>>
>> On 15 October 2014 09:27, Helen Mann <[log in to unmask]<mailto:[log in to unmask]>> wrote:
>> Hi,
>>
>> I have three groups low/medium/high and their yes/no answer to questions.
>>
>> If I do a multinomial logistic regression for each question and lump in other things such as "age", "gender" etc. does that interfere with my model (like it would if you added things in a normal linear regression?). As I have loads of IV's I thought I would lump them all into the one analysis to save time - thinking that as it's all to do with odds ratios that there would be no looking for interactions between the IV's on the DV (e.g. if group and gender was there it would look at group on answer and gender on answer but not affect of group and gender on answer)...I have found this from Strathclyde University (https://www.strath.ac.uk/aer/materials/5furtherquantitativeresearchdesignandanalysis/unit6/multinomiallogisticregression/) and have been trying to follow it but I think what is confusing me is this idea of model fit...what does it mean by model fit??? Why do I want the model likelihood ratio test to be non significant.
>>
>> What I'm interested in mainly is does group membership affect their yes/no answer - does it complicate things to add in other variables? If I had continuous data I would run an ANOVA but alas its categorical...
>>
>> Help!
>> Helen
>> This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham.
>>
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>> may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation.
>>
>> ------------------------------
>>
>> End of PSYCH-POSTGRADS Digest - 15 Oct 2014 to 16 Oct 2014 (#2014-211)
>> **********************************************************************
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