[R] predict function in regression analysis

[Bert Gunter]

 I think you want CI's for intercepts, not "means" (what is a "mean"
for a line??). If so, the ?confint function will give this to you for
the lot effect estimates when applied to a model fitted without an
intercept:

myfit <-lm(y~ lot-1+time)
confint(myfit)


Further discussion should be directed to a statistical site or a local
statistician, as these are not R issues.

Cheers,
Bert


Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374

"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll




On Tue, May 5, 2015 at 9:53 AM, li li <hannah.hlx at gmail.com> wrote:
> Hi all,
>   I have the following data in which there is one factor lot with six
> levels and one continuous convariate time.
> I want to fit an Ancova model with common slope and different intercept. So
> the six lots will have seperate paralell
> regression lines.I wanted to find the upper 95% confidence limit for the
> mean of the each of
> the regression lines. It doesnot seem straightforward to achieve this using
> predict function. Can anyone give some suggestions?
>
>   Here is my data. I only show the first 3 lots. Also I show the model I
> used in the end. Thanks very much!
>      Hanna
>
>       y lot time
>  [1,] 4.5   1    0
>  [2,] 4.5   1    3
>  [3,] 4.7   1    6
>  [4,] 6.7   1    9
>  [5,] 6.0   1   12
>  [6,] 4.4   1   15
>  [7,] 4.1   1   18
>  [8,] 5.3   1   24
>  [9,] 4.0   2    0
> [10,] 4.2   2    3
> [11,] 4.1   2    6
> [12,] 6.4   2    9
> [13,] 5.5   2   12
> [14,] 3.5   2   15
> [15,] 4.6   2   18
> [16,] 4.1   2   24
> [17,] 4.6   3    0
> [18,] 5.0   3    3
> [19,] 6.2   3    6
> [20,] 5.9   3    9
> [21,] 3.9   3   12
> [22,] 5.3   3   15
> [23,] 6.9   3   18
> [24,] 5.7   3   24
>
>
>> mod <- lm(y ~ lot+time)
>> summary(mod)
> Call:
> lm(formula = y ~ lot + time)
> Residuals:
>     Min      1Q  Median      3Q     Max
> -1.5666 -0.3344 -0.1343  0.4479  1.8985
> Coefficients:
>             Estimate Std. Error t value Pr(>|t|)
> (Intercept)  4.74373    0.36617  12.955 2.84e-14 ***
> lot2        -0.47500    0.41129  -1.155   0.2567
> lot3         0.41250    0.41129   1.003   0.3234
> lot4         0.96109    0.47943   2.005   0.0535 .
> lot5         0.98109    0.47943   2.046   0.0490 *
> lot6        -0.09891    0.47943  -0.206   0.8379
> time         0.02586    0.02046   1.264   0.2153
> ---
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.