Re: [R] Fixed effects regression constant (intercept) using lfe::felm

On 2020-07-09 07:15 -0700, Bert Gunter wrote: > On Thu, Jul 9, 2020 at 3:09 AM Valerio Leone Sciabolazza > wrote: > > > > When calculating a panel data > > regression with multiple fixed > > effects using the function felm() > > from the lfe package, no constant > > term (i.e. intercept)

Re: [R] Fixed effects regression constant (intercept) using lfe::felm

While you may get lucky here, your experience on SO indicates that you may do better by contacting the package maintainer (?maintainer) and asking him/her to refer you to appropriate references, as this sounds like a statistical methodology query. Bert Gunter "The trouble with having an open

[R] Fixed effects regression constant (intercept) using lfe::felm

Dear list users, When calculating a panel data regression with multiple fixed effects using the function felm() from the lfe package, no constant term (i.e. intercept) is generated in the summary results. In an old post on stackoverflow [1], someone suggested that it is possible to retrieve the

[R] Fixed effects in negative binomial mixed model mgcv::gam

I am using gam from the mgcv package to analyze a dataset with 24 entries : ran f1 f2 y 1 30005 545 1 300010 1045 1 1 5 536 1 1 10 770 2 30005 842 2 300010 2042 2 1 5 615 2 1 10 1361 3 30005 328 3 300010

Re: [R] Fixed Effects in lme function

li li gmail.com> writes: > > Dear all, > For the data below, I would like to fit a model with common > random slope and common random intercept as shown below. I am > interested in obtaining separate fixed effect estimates (intercept > and slope and corresponding hypothesis test) for each

[R] Fixed Effects in lme function

Dear all, For the data below, I would like to fit a model with common random slope and common random intercept as shown below. I am interested in obtaining separate fixed effect estimates (intercept and slope and corresponding hypothesis test) for each method. Instead of performing the

[R] Fixed effects regression with state-specific trends

Dear All, I am trying to implement a regression with state-specific trends in R. I can implement this in Stata with ease, but I am hoping to preserve my R workflow. I suspect there is an "R formula trick" that I'm just not understanding and I would be grateful to anyone who could help me

Re: [R] Fixed effects estimators doesn't drop or omit

computer. John Kane Kingston ON Canada > -Original Message- > From: alexier...@hotmail.com > Sent: Sun, 1 Nov 2015 18:40:36 + > To: r-help@r-project.org > Subject: [R] Fixed effects estimators doesn't drop or omit > > The title says it all, really. Fixed effects in

Re: [R] Fixed effects estimators doesn't drop or omit

You might get better or quicker answers if you ask package-specific questions to the maintainer of the package > maintainer("plm") [1] "Yves Croissant " or to the authors listed in > packageDescription("plm") Package: plm Version: 1.4-0 Date: 2013-12-24

Re: [R] Fixed effects regression and robust regression

since the OLS and robust regressions have the same number of DFs, looking at the residual standard error is insightful. Sadly not. The residual scale in a robust model is only partly indicative of goodness of fit; robust models intentionally downweight outliers. Much of the difference in

[R] Fixed effects regression and robust regression

Hello: I am using R 3.0.2.   I have panel data on countries' renewable energy net generation (and installed capacity) over time.  I am regressing these dependent variables on various socioeconomic variables, as well as binary policy variables.  I have have done basic OLS, but I wanted to

Re: [R] Fixed effects regression and robust regression

On Tue, May 19, 2015 at 1:23 PM, michael westphal via R-help r-help@r-project.org wrote: You can't compare them (statistically -- you can of course draw pictures). Note, from ?rlm: Note that the df.residual component is deliberately set to NA to avoid inappropriate estimation of the residual

[R] Fixed Effects using AER's Tobit function - system is singular

I have an unbalanced panel of daily, county data that is naturally bounded at zero so my intention is to use a tobit. I'm using tobit from the AER package. There is cyclicality in the data for each pattern that I would like to control for before I add my variables of interest. I run the

Re: [R] fixed effects with clustered standard errors

# -- Message: 28 Date: Tue, 07 Feb 2012 15:35:07 +0100 From: [hidden email] To: [hidden email] Subject: [R] fixed effects with clustered standard errors Message-ID: [hidden email] Content-Type: text/plain; charset=utf-8 Dear R-helpers, I have a very simple question and I

Re: [R] fixed effects linear model in R

Dear Andrew, Thanks for your suggestion. I will indeed have a look at Allison's booklet... Best, On 7 February 2012 23:39, Andrew Miles rstuff.mi...@gmail.com wrote: Based on Paul Allison's booklet Fixed Effect Regression Models (2009), the FE model can be estimated by person-mean centering

Re: [R] fixed effects with clustered standard errors

model   femod-lm(My~MX-1)   return(femod) } ### end test function Best, Giovanni ### original message # -- Message: 28 Date: Tue, 07 Feb 2012 15:35:07 +0100 From: [hidden email] To: [hidden email] Subject: [R] fixed

[R] fixed effects with clustered standard errors

-help@r-project.org Subject: [R] fixed effects with clustered standard errors Message-ID: 20120207143507.142...@gmx.com Content-Type: text/plain; charset=utf-8 Dear R-helpers, I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect

[R] fixed effects with clustered standard errors

Dear R-helpers, I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect regression model with clustered standard errors by individuals. For those using Stata, the counterpart would be xtreg with the fe option, or areg with the

[R] fixed effects linear model in R

Dear R-helpers, First of all, sorry for those who have (eventually) already received that request. The mail has been bumped several times, so I am not sure the list has received it... and I need help (if you have time)! ;-) I have a very simple question and I really hope that someone could

Re: [R] fixed effects linear model in R

Based on Paul Allison's booklet Fixed Effect Regression Models (2009), the FE model can be estimated by person-mean centering all of your variables (but not the outcome), and then including a random intercept for each person. The centering gives you the FE model estimates, and the random

[R] Fixed effects using Within transformation in PLM package

Hi all, I am trying to do my own fixed effects regression using the Within function in PLM. I apply the Within function to all my pseries and then run OLS on the transformed vectors using lm(). When I compare the results to those obtained via plm (within), the estimates are not always the same.

[R] Fixed effects using Within transformation in PLM package

Dear R community, I am trying to do my own fixed effects regression using the Within function in PLM. I apply the Within function to all my pseries and then run OLS on the transformed vectors using lm(). When I compare the results to those obtained via plm (within), the estimates are not always

Re: [R] Fixed effects using Within transformation in PLM package

On 2011-07-28 06:21, Luca Deckert wrote: Dear R community, I am trying to do my own fixed effects regression using the Within function in PLM. I apply the Within function to all my pseries and then run OLS on the transformed vectors using lm(). When I compare the results to those obtained via

Re: [R] fixed effects Tobit, Honore style?

A cleaner and slightly more tested version is at http://davidhughjones.blogspot.com/2011/07/honore-style-fixed-effects-estimators.html David Hugh-Jones Research Associate CAGE, Department of Economics University of Warwick http://davidhughjones.googlepages.com On 13 July 2011 15:33, David

Re: [R] fixed effects Tobit, Honore style?

True! Here's my attempt -- use at your own risk. honore - function (b, dataset, x1, x2) { dxb - (x2 - x1) %*% b y1 - # insert your y variable here y2 - # insert your y variable here sum( (pmax(y1, dxb) - pmax(y2, dxb) - dxb)^2 + 2*(y1 dxb)*(dxb-y1)*y2 + 2*(y2

[R] fixed effects Tobit, Honore style?

Hi all, Is there any code to run fixed effects Tobit models in the style of Honore (1992) in R? (The original Honore article is here: http://www.jstor.org/sici?sici=0012-9682%28199205%2960%3A3%3C533%3ATLALSE%3E2.0.CO%3B2-2) Cheers David [[alternative HTML version deleted]]

Re: [R] fixed effects Tobit, Honore style?

Not that I know of, but the paper says that they are easy to compute. If you did, you could contribute the code. Best, Daniel David Hugh-Jones-3 wrote: Hi all, Is there any code to run fixed effects Tobit models in the style of Honore (1992) in R? (The original Honore article is here:

[R] Fixed Effects Estimations (in Panel Data)

: Mon, 24 May 2010 18:24:00 -0400 From: ivo welch ivo...@gmail.com To: r-help r-h...@stat.math.ethz.ch Subject: [R] Fixed Effects Estimations (in Panel Data) Message-ID: aanlktimnvyn0tnkmnwsbfkpmcwyuiobbf6bjlzyj5...@mail.gmail.com Content-Type: text/plain; charset=ISO-8859-1 dear readers---I

[R] Fixed Effects Estimations (in Panel Data)

dear readers---I struggled with how to do nice fixed-effects regressions in large economic samples for a while. Eventually, I realized that nlme is not really what I needed (too complex), and all I really wanted is the plm package. so, I thought I would share a quick example.

Re: [R] fixed effects regression

The 90,000 indicators are the interactions between 300 zip codes (= postal codes) and 300 month indices. - Roy On Mon, Mar 22, 2010 at 5:56 AM, Petr PIKAL petr.pi...@precheza.cz wrote: Hi r-help-boun...@r-project.org napsal dne 22.03.2010 01:01:00: Hi All: I am trying to move a model

Re: [R] fixed effects regression

for the regression. -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Roy Lowrance Sent: Sunday, March 21, 2010 8:01 PM To: r-help@r-project.org Subject: [R] fixed effects regression Hi All: I am trying to move a model from Stata to R

[R] fixed effects regression

Hi All: I am trying to move a model from Stata to R. It is a linear regression model with about 90,000 indicator variables. What is the best approach to follow in R? - Roy [[alternative HTML version deleted]] __ R-help@r-project.org mailing

[R] fixed effects regression

Hi everyone, I am running this fixed effects model in R. The thing is, my own code and the canned routine keep returning different estimates for the fixed effects factors and intercept. (The other variables' estimates and R^2 are the same!!! weird!!) I attach my own code, just in case. I am

Re: [R] fixed effects regression

/bill.venables/ -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of parkbomee Sent: Saturday, 7 February 2009 1:57 PM To: r-help@r-project.org Subject: [R] fixed effects regression Hi everyone, I am running this fixed effects model

[R] Fixed effects

Hello everyone! I would really appreciate it if someone knew where could I find the command in R in order to run a fixed effects regression. What format should my data have? I have looked through the manual and I could not find anything Thank you in advance, Petros [[alternative HTML

Re: [R] Fixed effects

help.search('fixed effect') creates these matches. Does one of the do what you want? Help files with alias or concept or title matching 'fixed effect' using fuzzy matching: fixef(lme4)Extract Fixed Effects lmer(lme4) Fit (Generalized) Linear