Or
library(multgee)
fitord <- ordLORgee(Ideo_Ordinal~ Machiavellianism+Psychopathy+Narcissism,
data=RightWomen,
id= Politician_ID,repeated=Country_ID)
summary(fitord)
Should I use dta$Ideo_Ordinal <- ordered(factor(dta$Ideo_Ordinal)) ?
Στις Δευ, 6 Αυγ 2018 στις 6:00 μ.μ., ο/η euthymios kasvikis <
euthymios.k.kasvi...@gmail.com> έγραψε:
> First of all thanks for your advice. So suppose that I would like to use
> the multgee package. The model would be like:
> library(multgee)
> fitord <- ordLORgee(Ideo_Ordinal~ Machiavellianism+Psychopathy+Narcissism,
> data=RightWomen,
> id= ordered(factor(Country_ID)))
> summary(fitord)
>
> Στις Δευ, 6 Αυγ 2018 στις 7:29 π.μ., ο/η Duncan Mackay <
> dulca...@bigpond.com> έγραψε:
>
>> Hi
>>
>> Please read the geepack manual carefully.
>> GEE ordinal regression is not simple.
>> You need to format your data and do not use sample as a storage name. It
>> is
>> the name of a function
>>
>> dta is storage
>> dta$Ideo_Ordinal <- ordered(factor(dta$Ideo_Ordinal))
>>
>> m0 <-
>> ordgee(Ideo_Ordinal ~ Machiavellianism+Psychopathy+Narcissism ,data = dta,
>> id = Country_ID,
>> corstr = "independence")
>>
>> You need to see if the model is appropriate first and whether the sandwich
>> errors are right before you go further
>>
>> If this is your data you may not get credible results.
>> You need to read up on the requirements of GEEs and ordinal GEEs in
>> particular
>> There are a number of packages with different data requirements and
>> methods
>> If you have repeated measurements repolr; ?multgee (just from memory)
>> Small sample sizes are a problem there are a number of packages dealing
>> with
>> this but you will have to see which is best for you
>> Many do not offer a method for ordinal or multinomial GEE.
>> One further question to ask population specific or subject specific ie
>> to
>> GEE or not to GEE
>>
>>
>> Regards
>>
>> Duncan
>>
>> Duncan Mackay
>> Department of Agronomy and Soil Science
>> University of New England
>> Armidale NSW 2350
>>
>>
>>
>> -----Original Message-----
>> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of euthymios
>> kasvikis
>> Sent: Saturday, 4 August 2018 07:30
>> To: r-help@r-project.org
>> Subject: [R] Perform GEE regression in R with multiple dependent variables
>>
>> Im trying to perform generalized estimating equation (GEE) on the (sample)
>> dataset below with R and I would like some little guidance. First of all I
>> will describe my dataset. As you can see below it includes 5 variables.
>> Country_ID shows the country of the politician, Ideo_Ordinal his poltical
>> belief from 1 to 7 (far left to far right). Then we have measurements
>> regarding three characteristics. I would like to run an analysis based on
>> the country and the political beliefs of every politician (dependent
>> variables) in relation with the 3 characteristics. I have used the geepack
>> package using:
>>
>> library(geepack)
>>
>> samplem<-coef(summary(geeglm(sample$Ideo_Ordinal
>> ~Machiavellianism+Psychopathy+Narcissism ,data = sample, id =
>> sample$Ideo_Ordinal,
>> corstr = "independence"))) %>%
>> rownames_to_column() %>%
>> mutate(lowerWald = Estimate-1.96*Std.err, # Lower Wald CI
>> upperWald=Estimate+1.96*Std.err, # Upper Wald CI
>> df=1,
>> ExpBeta = exp(Estimate)) %>% # Transformed estimate
>> mutate(lWald=exp(lowerWald), # Upper transformed
>> uWald=exp(upperWald)) # Lower transformed
>> samplem
>>
>> I would like to know if it is valid to add in this method the Country_ID
>> simultaneously with Ideo_Ordinal and how to do it.
>>
>> Country_ID Ideo_Ordinal Machiavellianism Narcissism Psychopathy
>> 3 1 3 0.250895132 0.155238716
>> 0.128683755
>> 5 1 3 -0.117725000 -0.336256435
>> -0.203137879
>> 7 1 3 0.269509029 -0.260728261
>> 0.086819555
>> 9 1 6 0.108873496 0.175528190
>> 0.182884928
>> 14 1 3 0.173129951 0.054468468
>> 0.155030794
>> 15 1 6 -0.312088872 -0.414358301
>> -0.212599946
>> 17 1 3 -0.297647658 -0.096523143
>> -0.228533352
>> 18 1 3 -0.020389157 -0.210180866
>> -0.046687695
>> 20 1 3 -0.523432382 -0.125114982
>> -0.431070629
>> 21 1 1 0.040304508 0.022743463
>> 0.233657881
>> 22 1 3 0.253695988 -0.330825166
>> 0.101122320
>> 23 1 3 -0.478673895 -0.421801231
>> -0.422894791
>> 27 1 6 -0.040856419 -0.566728704
>> -0.136069484
>> 28 1 3 0.240040249 -0.398404825
>> 0.135603114
>> 29 1 6 -0.207631653 -0.005347621
>> -0.294935155
>> 30 1 3 0.458042533 0.462935386
>> 0.586244831
>> 31 1 3 -0.259850232 -0.233074787
>> -0.092249465
>> 33 1 3 0.002164223 -0.637668706
>> -0.267158031
>> 34 1 6 0.050991955 -0.098030021
>> -0.043826848
>> 36 1 3 -0.338052871 -0.168894328
>> -0.230198200
>> 38 1 3 0.174382347 0.023807812
>> 0.192963609
>> 41 2 3 -0.227322148 -0.010016330
>> -0.095576329
>> 42 2 3 -0.267514920 0.066108837
>> -0.218979873
>> 43 2 3 0.421277754 0.385223920
>> 0.421274111
>> 44 2 3 -0.399592341 -0.498154998
>> -0.320402699
>> 45 2 1 0.162038344 0.328116118
>> 0.104105963
>> 47 2 3 -0.080755709 0.003080287
>> -0.043568723
>> 48 2 3 0.059474124 -0.447305420
>> 0.003988071
>> 49 2 3 -0.219773040 -0.312902659
>> -0.239057883
>> 51 2 3 0.438659431 0.364042111
>> 0.393014172
>> 52 2 3 -0.088560903 -0.490889275
>> -0.006041054
>> 53 2 3 -0.122612591 0.074438944
>> 0.103722836
>> 54 2 3 -0.450586055 -0.304253061
>> -0.132365179
>> 55 2 6 -0.710545197 -0.451329850
>> -0.764201786
>> 56 2 3 0.330718447 0.335460128
>> 0.429173481
>> 57 2 3 0.442508023 0.297522144
>> 0.407155726
>> 60 2 3 0.060797815 -0.096516876
>> -0.012802977
>> 61 2 3 -0.250757764 -0.113219864
>> -0.215345379
>> 62 2 1 0.153654345 -0.089615287
>> 0.118626045
>> 65 2 3 0.042969508 -0.486999608
>> -0.080829636
>> 66 3 3 0.158337022 0.208229002
>> 0.241607154
>> 67 3 3 0.220237408 0.397914524
>> 0.262207709
>> 69 3 3 0.200558577 0.244419633
>> 0.301732113
>> 71 3 3 0.690244689 0.772692418
>> 0.625921098
>> 72 3 3 0.189810070 0.377774321
>> 0.293988340
>> 73 3 3 -0.385724422 -0.262131032
>> -0.373159652
>> 74 3 3 -0.124095769 -0.109816334
>> -0.127157915
>> 75 3 1 0.173299879 0.453592671
>> 0.325357383
>> 76 3 3 -0.598215129 -0.643286651
>> -0.423824759
>> 77 3 3 -0.420558406 -0.361763025
>> -0.465612116
>> 78 3 3 -0.176788569 -0.305506924
>> -0.203730879
>> 80 3 3 -0.114790731 0.262392918
>> 0.061382073
>> 81 3 3 -0.274904173 -0.342603918
>> -0.302761994
>> 82 3 3 -0.146902101 -0.059558818
>> -0.120550957
>> 84 3 3 0.038303792 -0.139833875
>> 0.170005914
>> 85 3 3 -0.220212221 -0.541399757
>> -0.555201764
>> 87 3 3 0.255300386 0.179484246
>> 0.421428096
>> 88 3 6 -0.548823069 -0.405541620
>> -0.322935805
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
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