Why isn't the Anova() function in the Car package returning an F statistic? I ran a simple psychology experiment that included 4 conditions, each containing 8 blocks of training. There were different participants in each condition. Hence, condition and block and subject and block are crossed, but subject is nested in condition. I'm trying to do a basic repeated measures anova to test for effects of block and condition. I have an unbalanced design, and a mixed effects model. My approach was to use the lme4 package in conjunction with the car package. I am running R version 2.14 on mac os x lion.
Here is what I've done:
library(nlme)
library(car)

rm( list = ls() )

data <- read.table("anova_data", header = TRUE)

condition <- factor(data$condition)
block <- factor(data$block)
subject <- factor(data$subject)
accuracy <- data$accuracy

fm1 <- lmer( accuracy ~ block*condition + (1|subject %in% condition) )

Anova(fm1)

My problem is that this returns a summary table without F values, like such:
Analysis of Deviance Table (Type II tests)

Response: accuracy

                 Chisq Df Pr(>Chisq)
     block           17.169  7    0.01634 *  

condition       68.294  3  9.897e-15 ***

block:condition 26.481 21    0.18869

Any help is greatly appreciated.
 A: Try MixMod package to get p-values.
Example
library(MixMod)
data(TVbo) 
library(lme4) 
m <- lmer(Cutting ~ TVset*Picture+(1|Assessor) + (1|Assessor:Picture) + (1|Assessor:TVset),data=TVbo) 
anovaTAB(m, TVbo)

Output
Analysis of Variance Table:
              NumDF DenDF F.value p.value    
TVset             2    14   20.01   1e-04 ***
Picture           3    21    2.87    0.06 .  
TVset:Picture     6   138    4.64   3e-04 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

A: car does support the F-statistic for analysis of deviance tables:
Anova(m, test.statistic="F")

Resulting in
Analysis of Deviance Table (Type II Wald F tests with Kenward-Roger df)

Response: some_response
                           F      Df Df.res  Pr(>F)    
some_factor1               0.30   1    3.4    0.6196    
some_factor2               26.94  1   78.5   1.6e-06 ***
some_factor1:some_factor2  9.66   1   79.4    0.0026 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

For which internally it uses the pbkrtest package.
