Greetings, I'd be grateful if a good Samaritan helps me to approach this problem....
with my data, I've created the following model lm(formula = OUTCOME ~ VAR1 + VAR2) summary(model) Call: lm(formula = OUTCOME ~ VAR1 + VAR2) Residuals: Min 1Q Median 3Q Max -1.4341 -0.3621 0.1879 0.4994 0.7696 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.89020 0.26826 7.046 5.92e-07 *** VAR1 0.04725 0.06001 0.787 0.440 VAR2 0.04139 0.05655 0.732 0.472 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.6618 on 21 degrees of freedom Multiple R-squared: 0.9474, Adjusted R-squared: 0.9424 F-statistic: 189.2 on 2 and 21 DF, p-value: 3.696e-14 but now, I need to predict OUTCOME (Y) when VAR1=8 and VAR2 =64; estimate the standard error of the predicted value, and construct a 95% CI Your help is much appreciated RG ***************************************** Ricardo L Gomez Center for International Education University of Massachusetts-Amherst Telephone: (413)545-0465 | Fax: (413)545-1263 Web Address http://www.umass.edu/cie E-mail: c...@educ.umass.edu Get the world's best email - http://nz.mail.yahoo.com/ ______________________________________________ R-help@r-project.org mailing list 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.
