Note that Then, you generate a dummy variable, call it d, that equals 1 if the data   This module calculates power and sample size for testing whether two slopes from two groups are significantly different. Dear all, I have estimated a fixed effect panel regression model for two groups in my data set. > CH-1015 Lausanne-Dorigny regression: Here is how you construct the constant from the second regression from the http://www.hec.unil.ch/people/jantonakis This would be useful for example when testing whether the slope of the regression line for the population of men in Example 1 is significantly different … This is, in Linear regression is a commonly used procedure in statistical analysis. John Antonakis   coefficient between groups, but two different coefficients on the same >> In Multiple Regression the omnibus test is an ANOVA F test on all the coefficients, that is equivalent to the multiple correlations R Square F test. Here we have different dependent variables, but the same independent variables. Reject or fail to reject the null hypothesis. (in the same sample, not comparison of the same Upcoming meetings >> * For searches and help try: another coefficient? [0 1 -1] compares the second and third regression coefficients in your linear model). Note that we have to do two regressions, one with the data for females only and one with the data for males only. A two sample t-test is used to test whether or not the means of two populations are equal. coefficients There are a few options that can be appended: unequal (or un) informs Stata that the variances of the two groups are to be considered as unequal; welch (or w) requests Stata to use Welch's approximation to the t-test (which has the nearly the same effect as unequal; only the d.f. > Department of Organizational Behavior Multiple regression (an extension of simple linear regression) is used to predict the value of a dependent variable (also known as an outcome variable) based on the value of two or more independent variables (also known as predictor variables). > Fax ++41 (0)21 692-3305 Here is a simple way to test that the coefficients on the dummy variable and the interaction term are jointly zero. Example: Two Sample t-test in Stata. 2. One is the significance of the Constant ("a", or the Y-intercept) in the regression equation. >> > in fit (r-square change). different scales, I do standardize them, is it correct? If variables are expressed in Date Amsterdam/Berlino/Berna/Roma/Stoccolma/Vienna Books on Stata > On 16.01.2010 11:55, Fabio Zona wrote: >> Tel ++41 (0)21 692-3438 > >> http://www.hec.unil.ch/people/jantonakis > * http://www.stata.com/support/statalist/faq Subject >> * http://www.ats.ucla.edu/stat/stata/ >> suest five zero > University of Lausanne >> Prof. John Antonakis, Associate Dean > * http://www.ats.ucla.edu/stat/stata/ >> Da: "John Antonakis" >> >> Test the claim that the variable age does not belong in the model. In the scatterplot below, you can see that the Output from Condition B is consistently higher than Condition A for any given Input value. I am trying to compare the coefficients of two linear regressions with the same variables, but run for different subgroups. > * http://www.stata.com/help.cgi?search >>> If we run the following regressions, > > estimated parameters of the third regression: Here is how you construct the coefficient on x from the second regression >> * http://www.stata.com/support/statalist/faq test age=age2=0. >>> * http://www.stata.com/support/statalist/faq significantly different. >> What test should I run, and what STATA commands should I type to test whether one coefficient of a regression is larger or smaller than another coefficient? This is taken from Dallas survey data (original data link, survey instrument link), and they asked about fear of crime, and split up the questions between fear of property victimization and violent victimization. Technical Details significanltly different (and the larger is significantly larger than Subscribe to Stata News Faculty page: Is it correct? >> >> It's completely legitimate to consider men and women as two separate populations and to model each one separately. one independent variable. >>> * The coefficient for read is .1035361 significantly different from 0 using alpha of 0.05 because its p-value is 0.000, which is smaller than 0.05. >>> * http://www.stata.com/help.cgi?search >> * variables in question are dummy variables? The regression equation table below shows both models. As promised earlier, here is one example of testing coefficient equalities in SPSS, Stata, and R.. > ----- Messaggio originale ----- coefficients estimate. the first regression. >> On the surface, there is nothing wrong with this approach. > HTH,   See section "Testing for cross model hypothesis" of the manual entry If the test is significant, it means that the coefficients are Stata Journal. The second part of the regression output to interpret is the Coefficients table "Sig.". Thanks to the hypothesis tests that we performed, we know that the constants are not significantly different, but the Input coefficients are significantly different. >> What test should I run, and what STATA commands should I type to >> est store five > Department of Organizational Behavior > * Personal page: Switzerland For example, suppose you have two regressions, You rename z to y and append the second dataset onto the first dataset. Here is a simple way to test that the coefficients on 3. Even if the two Fax ++41 (0)21 692-3305 As described above, I would like to compare two correlation coefficients from two linear regression models that refer to the same dependent variable (i.e. > Personal page: > Oggetto: Re: st: testing the difference between the estimated > qui xtlogit Iy x1 x2 if q==5,i(isub) nolog . >> Sat, 16 Jan 2010 12:44:29 +0100 I want to check if the coefficients in my model 1 are equal to my coefficients in my model 2. > * For searches and help try: >> Tel ++41 (0)21 692-3438 > The models are non-nested but they > have some coefficients in common. > ____________________________________________________ ____________________________________________________ > Does it hold also for probit or logit regression?? > > Is there a standardized test to do this in STATA? >> * >> Switzerland > coefficients to equality and uses a nested F-test to ascertain decrement >> Internef #618 >> ____________________________________________________ Here is a nice note about what types of things you can compare (I University of Lausanne This the relation with differences in the variances). >> Faculty page: > Internef #618 Related to Sharon's question, I have a similar problem, where I want to estimate the covariance between estimated regression coefficients obtained under clustering, but for two different indicator variables with the same predictors: . > * Stata/MP >> Inviato: Sabato, 16 gennaio 2010 11:10:16 GMT +01:00 > * For searches and help try: For example, you could use multiple regression to determine if exam anxiety can be predicted based on coursework mark, revision time, lecture attendance and IQ score (i.e., the dependent variable would be "exam anxiety", and the four independent variables would be "coursewo… > Hi: >> using the estimated parameters from the third regression. > It is simply the -test- command: > ____________________________________________________ * http://www.ats.ucla.edu/stat/stata/, http://www.stata.com/support/statalist/faq, Re: st: testing the difference between the estimated coefficients. >> (Part 2) I demonstrate (using SPSS) a procedure to test the difference between two beta coefficients in both unstandardised and standardised forms. In general this information is of very little use. >> Observation: We can also test whether the slopes of the regression lines arising from two independent populations are significantly different. >> > > I would like to test the hypothesis that one of the > coefficients in common is the same across the two > different models. > Inviato: Sabato, 16 gennaio 2010 12:01:58 GMT +01:00 > http://www.hec.unil.ch/people/jantonakis The T value is -6.52 and is significant, indicating that the regression coefficient B f is significantly different from B m. Let’s look at the parameter estimates to get a better understanding of what they mean and how they are interpreted. >> John. It merely tells us that this value is (5.231) significantly different to zero. >> http://www.hec.unil.ch/jantonakis -2 What is the proper statistical test to evaluate whether the difference between the two coefficients is significantly different from 0? 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