Diagnostics: R and Phoenix [Study Assessment]
Hi ElMaestro et al.,
I can only provide the results of R and Phoenix:
R 3.2.5
Phoenix 6.47.0.768
Estimates and their SEs are exactly the same. CIs are not (due to different DFs?).
PS: An ideas how to weight by
❝ Extract some model diagnostics: DF's and LogLikelihood, and compare to find out which result is the better candidate.
I can only provide the results of R and Phoenix:
R 3.2.5
library(nlme)
Subj <- c(1, 2, 4, 5, 6, 4, 5, 6, 7, 8, 9, 7, 8, 9)
Dose <- c(25, 25, 50, 50, 50, 250, 250, 250, 75, 75, 75, 250, 250, 250)
AUC <- c(326.40, 437.82, 557.47, 764.85, 943.59, 2040.84, 2989.29,
4107.58, 1562.42, 982.02, 1359.68, 3848.86, 4333.10, 3685.55)
Cmax <- c(64.82, 67.35, 104.15, 143.12, 243.63, 451.44, 393.45,
796.57, 145.13, 166.77, 296.90, 313.00, 387.00, 843.00)
resp <- data.frame(Subj, Dose, Cmax, AUC)
resp$Subj <- factor(resp$Subj)
muddle <- lme(log(Cmax) ~ log(Dose), data=resp, random=~1|Subj)
sum.muddle <- summary(muddle)
CI.muddle <- intervals(muddle, level=0.9, which="fixed")
print(sum.muddle); CI.muddle$fixed[, ]
Linear mixed-effects model fit by REML
Data: resp
AIC BIC logLik
14.24355 16.18317 -3.121774
Random effects:
Formula: ~1 | Subj
(Intercept) Residual
StdDev: 0.3347319 0.1206792
Fixed effects: log(Cmax) ~ log(Dose)
Value Std.Error DF t-value p-value
(Intercept) 1.9413858 0.24314072 7 7.984618 1e-04
log(Dose) 0.7617406 0.04727976 5 16.111347 0e+00
Correlation:
(Intr)
log(Dose) -0.863
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-1.07547728 -0.35579449 -0.03301391 0.45088601 0.91853654
Number of Observations: 14
Number of Groups: 8
lower est. upper
(Intercept) 1.4807366 1.9413858 2.4020350
log(Dose) 0.6664696 0.7617406 0.8570116
Phoenix 6.47.0.768
Model Specification and User Settings
Dependent variable : logCmax
Transform : None
Fixed terms : int+logDose
Random/repeated terms : Subject
Denominator df option : satterthwaite
Class variables and their levels
Subject : 1 2 4 5 6 7 8 9
Final variance parameter estimates:
Var(Subject) 0.112045
Var(Residual) 0.0145635
REML log(likelihood) -0.623363
-2* REML log(likelihood) 1.24673
Akaike Information Crit. 9.24673
Schwarz Bayesian Crit. 11.1864
Effect:Level Estimate StdError Denom_DF T_stat P_value Conf T_crit Lower_CI Upper_CI
---------------------------------------------------------------------------------------------
int 1.9413858 0.2431407 9.2 7.98462 1.980E-5 90 1.829 1.4967592 2.3860125
logDose:logDose 0.7617406 0.0472798 5.9 16.11135 4.241E-6 90 1.949 0.6695783 0.8539029
Estimates and their SEs are exactly the same. CIs are not (due to different DFs?).
PS: An ideas how to weight by
1/log(Dose)
in lme()
? Suggested by Chow/Liu and gives me a better fit in Phoenix.—
Dif-tor heh smusma 🖖🏼 Довге життя Україна!![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- Dose Proportionality and Variance AngusMcLean 2016-05-11 16:55 [Study Assessment]
- More information, please Helmut 2016-05-12 14:34
- More information, please AngusMcLean 2016-05-13 16:40
- Setup in Phoenix/WinNonlin Helmut 2016-05-14 02:26
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-14 18:54
- Setup in Phoenix/WinNonlin Helmut 2016-05-15 14:47
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-15 15:17
- Phoenix 64 Warning Helmut 2016-05-15 15:56
- Phoenix 64 Warning AngusMcLean 2016-05-15 20:11
- OT: imperial vs. metric units Helmut 2016-05-16 16:26
- Phoenix 64 Warning AngusMcLean 2016-05-15 20:11
- Setup in Phoenix/WinNonlin ElMaestro 2016-05-15 20:54
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-15 22:30
- Phoenix 64 Warning Helmut 2016-05-15 15:56
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-15 15:17
- Setup in Phoenix/WinNonlin Helmut 2016-05-15 14:47
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-16 21:00
- NCSS vs. PHX/WNL vs. SAS Helmut 2016-05-17 01:50
- NCSS vs. PHX/WNL vs. SAS - Validation? mittyri 2016-05-18 08:23
- Diagnostics ElMaestro 2016-05-18 09:20
- Diagnostics: R and PhoenixHelmut 2016-05-18 15:14
- Diagnostics: R zizou 2016-05-22 19:07
- Diagnostics: R Helmut 2016-05-23 01:22
- SASian potpourri d_labes 2016-05-24 12:02
- Compilation Helmut 2016-05-24 14:27
- REML or not d_labes 2016-05-24 16:33
- complete or not Helmut 2016-05-24 16:57
- Compilation AngusMcLean 2016-05-26 16:46
- doubts about NCSS Helmut 2016-05-26 19:13
- Doubts about NCSS zizou 2016-05-26 23:38
- doubts about NCSS Helmut 2016-05-26 19:13
- Compilation AngusMcLean 2016-05-28 00:51
- Kenward-Roger? Helmut 2016-05-28 15:59
- 90% confidence interval for R_dnm Shuanghe 2019-01-04 17:45
- 90% confidence interval for R_dnm d_labes 2019-01-05 14:01
- Visualizing lmer and limits mittyri 2019-01-06 17:00
- Visualizing lmer and limits Shuanghe 2019-01-07 11:05
- Visualizing lmer and limits d_labes 2019-01-07 15:08
- Visualizing lmer and limits mittyri 2019-01-13 23:53
- 90% confidence interval for R_dnm Shuanghe 2019-01-07 10:53
- 90% confidence interval for R_dnm d_labes 2019-01-07 15:17
- 90% confidence interval for R_dnm Shuanghe 2019-01-07 17:11
- 90% confidence interval for R_dnm d_labes 2019-01-07 18:24
- offtop: greek letters and tables mittyri 2019-01-08 00:19
- OT: greek letters and symbols Helmut 2019-02-02 16:04
- 90% confidence interval for R_dnm Shuanghe 2019-01-07 17:11
- 90% confidence interval for R_dnm d_labes 2019-01-07 15:17
- Visualizing lmer and limits mittyri 2019-01-06 17:00
- 90% confidence interval for R_dnm d_labes 2019-01-05 14:01
- REML or not d_labes 2016-05-24 16:33
- Compilation Helmut 2016-05-24 14:27
- SASian potpourri d_labes 2016-05-24 12:02
- Diagnostics: R Helmut 2016-05-23 01:22
- Diagnostics: R zizou 2016-05-22 19:07
- Diagnostics: R and PhoenixHelmut 2016-05-18 15:14
- Smith’s paper Helmut 2016-05-18 14:44
- Smith’s paper d_labes 2019-01-05 15:00
- Diagnostics ElMaestro 2016-05-18 09:20
- NCSS vs. PHX/WNL vs. SAS - Validation? mittyri 2016-05-18 08:23
- NCSS vs. PHX/WNL vs. SAS Helmut 2016-05-17 01:50
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-14 18:54
- Setup in Phoenix/WinNonlin Helmut 2016-05-14 02:26
- More information, please AngusMcLean 2016-05-13 16:40
- More information, please Helmut 2016-05-12 14:34