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From |
Cameron McIntosh <cnm100@hotmail.com> |

To |
STATA LIST <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Regressions with dependent continuous variable with bounded range |

Date |
Mon, 19 Dec 2011 12:47:37 -0500 |

There is a free 7-day trial of Neusrel available right now... you do need Matlab to run it, however.Cam ---------------------------------------- > Date: Mon, 19 Dec 2011 11:58:10 -0500 > Subject: Re: st: Regressions with dependent continuous variable with bounded range > From: sroy2138@gmail.com > To: statalist@hsphsun2.harvard.edu > > Cam, > This is very interesting indeed! I had thought of SEM, but not this. > > Sincerely, > Suryadipta. > > On Mon, Dec 19, 2011 at 9:46 AM, Cameron McIntosh wrote: > > An explorative approach to non-linearity might also be worth considering: > > Buckler, F., & Hennig-Thurau, T. (2008). Identifying Hidden Structures in Marketing’s Structural Models Through Universal Structure Modeling: An Explorative Bayesian Neural Network Complement to LISREL and PLS. Marketing -- Journal of Research and Management, 4(2), 47-66.http://www.neusrel.com/index.html > > > > Cam > >> Date: Mon, 19 Dec 2011 08:52:42 -0500 > >> Subject: Re: st: Regressions with dependent continuous variable with bounded range > >> From: sroy2138@gmail.com > >> To: statalist@hsphsun2.harvard.edu > >> > >> Dear David, > >> Thank you very much for the useful suggestions! I completely > >> understand the points that have made, and will definitely explore > >> them. Actually, the incorporation of the quadratic x is driven by the > >> theoretical hypothesis, which has implications for the signs of x and > >> x-squared. A basic scatter diagram: twoway scatter y x, by(year) also > >> suggests non-linearity. I, of course, start with the linear form. We > >> can also probably compare between the models on the basis of LR tests, > >> or AIC/BIC criteria. Interestingly, a logit regression of the form > >> that Nick suggested gives me the (statistically significant) expected > >> signs of the coefficients. However, I would have to check the > >> robustness etc. > >> > >> Best regards, > >> Suryadipta. > >> > >> On Sun, Dec 18, 2011 at 2:11 PM, David Hoaglin wrote: > >> > Dear All, > >> > > >> > Is it well-established that the effect is quadratic in x, as opposed > >> > to being nonlinear in x (the functional form might be quadratic or > >> > something else entirely)? If the form is not necessarily quadratic, a > >> > good strategy would fit the linear term in x and then examine the > >> > pattern of nonlinearity by plotting the residuals against x. A > >> > quadratic term can provide a reasonable approximation for some > >> > patterns of nonlinearity, but not for others. > >> > > >> > Also, centering x at a suitable value (often near the middle of its > >> > range) would be a good preliminary step. > >> > > >> > David Hoaglin > >> > > >> > On Sun, Dec 18, 2011 at 11:56 AM, Suryadipta Roy wrote: > >> >> Dear Brendan and Nick, > >> >> > >> >> Thank you so much for the detailed suggestions! I will try to > >> >> implement these. Infact, I was just reading the paper by Papke and > >> >> Wooldridge (Journal of Econometrics, 2008) "Panel data methods for > >> >> fractional response variables with an application to test pass rates" > >> >> in order to understand the application better. > >> >> > >> >> Best regards, > >> >> Suryadipta. > >> > * > >> > * For searches and help try: > >> > * http://www.stata.com/help.cgi?search > >> > * http://www.stata.com/support/statalist/faq > >> > * http://www.ats.ucla.edu/stat/stata/ > >> > >> * > >> * For searches and help try: > >> * http://www.stata.com/help.cgi?search > >> * http://www.stata.com/support/statalist/faq > >> * http://www.ats.ucla.edu/stat/stata/ > > > > * > > * For searches and help try: > > * http://www.stata.com/help.cgi?search > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Regressions with dependent continuous variable with bounded range***From:*Suryadipta Roy <sroy2138@gmail.com>

**References**:**st: Regressions with dependent continuous variable with bounded range***From:*Suryadipta Roy <sroy2138@gmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*brendan.halpin@ul.ie (Brendan Halpin)

**Re: st: Regressions with dependent continuous variable with bounded range***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*Suryadipta Roy <sroy2138@gmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*brendan.halpin@ul.ie (Brendan Halpin)

**Re: st: Regressions with dependent continuous variable with bounded range***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*Suryadipta Roy <sroy2138@gmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*David Hoaglin <dchoaglin@gmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*Suryadipta Roy <sroy2138@gmail.com>

**RE: st: Regressions with dependent continuous variable with bounded range***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: st: Regressions with dependent continuous variable with bounded range***From:*Suryadipta Roy <sroy2138@gmail.com>

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