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From |
Rozilee Asid <rozilee@streamyx.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Quadratic term validity |

Date |
Thu, 11 Nov 2004 06:06:47 +0800 |

Thanks Nick and SamL. At first, I've tried not to include the Ln term and found that the model suffer with the misspecification problem when I invoke linktest and ovtest command and the single and quadratic term of age shows the same sign as model 2 just now. That come my idea to modified the variable into ln form. Off course my model more likely to test the human capital theory from the perspectives of non-technical workers in the industrial sectors. Anyway thank for your comment and advice. I'll take it seriously. Thanks guys Rozilee On 11/11/04 5:37 AM, "SamL" <saml@demog.berkeley.edu> wrote: > Well, um, actually, there is an economic theoretic reason for the > quadratic term in age, drawn from (among other sources) human capital > theory--declining returns to _________________ (experience, prior > training, fill in the blank with what you mean age to signify). So, I'm > not sure I'd drop the linear term, as the theory does not imply only > curving returns. > > There may be other economic theories that justify the quadratic and the > linear term. > > Finally, statistically, removng the linear term implies no main effect. > Does that make sense? It might help to graph the results. I think no > linear term would be a major problem, but maybe not. > > HTH. > Sam > > On Wed, 10 Nov 2004, Nick Cox wrote: > >> Are you really dealing with age or ln age? >> >> "Valid" or not depends on your criteria of >> validity, which are not explicit. From what >> I gather people like using quadratics in income >> versus age because they often fit fairly well, >> and there isn't a economic theory reason >> for the functional form. So you could make >> a case for dropping the linear term >> if it doesn't to seem to help with the fit. >> >> On the other hand, there are several grounds >> for being more circumspect: >> >> 1. Just because the linear term looks >> insignificant does not mean that the >> model with quadratic term alone is necessarly >> better, all things considered. >> >> 2. The P-value is just one indicator. You >> don't say anything about the change in R^2 >> or RMS error or (probably most important of >> all) where there is clear structure >> if you plot >> >> residuals from model with quadratic >> term alone >> >> versus >> >> age. >> >> 3. Inferences are surely complicated by >> the correlation between age and age^2. >> >> 4. There are good discussions of related >> issues in McCullagh and Nelder's book >> on generalised linear models and in >> Nelder's paper in American Statistician >> November 1998. Loosely, there are >> grounds for treating polynomial terms >> as yoked together like a team, although Nelder >> puts it better than that. >> >> Nick >> n.j.cox@durham.ac.uk >> >> Rozilee Asid >> >>> My wage model consists of several variables and model. One of my model >>> consists of quadratic term of age, example >>> Ln-wage = alpha0 + alpha1.ln_age + alpha2.ln_exp (model 1) >>> Ln_wage = alpha0 + alpha1.ln_age + alpha2.ln_exp + >>> alpha3.ln_age^2 (model 2) >>> >>> My main attention is to identified whether age play its >>> significant role in >>> the model. When I regress the model I found that alpha1 coefficient is >>> negative and insignificant and alpha3 is positive and significant. My >>> question is before I include the quadratic term of age >>> variable (model 1), >>> the alpha1 coefficient is positive and significant. >>> >>> Is it valid for me to report the finding from model 2 >>> equations, especially >>> when alpha1 is negative in the model. >> >> * >> * For searches and help try: >> * http://www.stata.com/support/faqs/res/findit.html >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: RE: Quadratic term validity***From:*SamL <saml@demog.berkeley.edu>

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