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Question

I have an unbalanced dataset (4 groups in total, of which 3 groups consist of 8 rats and one group consists of 7 rats). I want to run a mixed ANOVA (type III) with the Car package. My dataset has 3 factors: Day (10 levels, within-subject factor), Sex (2 levels, between-subject factor) and Group (2 levels, between-subject factor). My dependent variable is Weight.

A subset of my data can be obtained with this code:

weight_gain_SI <- structure(list(Day = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L), levels = c("2", "3", "4", "5", "6", 
"7", "8", "9", "10", "11"), class = "factor"), Rat = structure(c(1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 
29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 
25L, 26L, 27L, 28L, 29L, 30L, 31L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L), levels = c("I0", 
"I1", "I2", "I3", "J0", "J1", "J2", "J3", "K0", "K1", "K2", "K3", 
"L0", "L1", "L3", "M0", "M1", "M2", "M3", "N0", "N1", "N2", "N3", 
"O0", "O1", "O2", "O3", "P0", "P1", "P2", "P3"), class = "factor"), 
    Weight = c(1.015921931, 1.011339093, 1.016291327, 1.019565217, 
    1.046148738, 1.011992005, 1.041567291, 1.023960067, 0.992353905, 
    0.972113503, 0.991992463, 1.00931677, 1.004423273, 0.994209809, 
    1.031988873, 1.036828645, 1.015625, 1.001497006, 1.004291845, 
    1.057726153, 1.04837595, 1.048746996, 1.046019483, 1.010251153, 
    1.024016352, 1.017249877, 1.011802575, 1.044538362, 1.043112513, 
    1.032426778, 1.039370079, 0.995377504, 1.021598272, 0.973646382, 
    0.970652174, 1.002324037, 0.988674217, 0.989778535, 0.988019967, 
    0.985800109, 0.989236791, 0.971267075, 0.996376812, 1.023817625, 
    0.991485014, 0.998609179, 1.053196931, 1.014616935, 0.989021956, 
    1.033798283, 1.065821894, 1.072909468, 1.057329214, 1.06886127, 
    1.017426961, 0.998978028, 1.049285362, 1.027896996, 1.057542263, 
    1.061338941, 1.057880056, 1.061280383, 0.996404725, 0.976781857, 
    0.972208912, 0.95923913, 0.983067729, 0.987341772, 0.97955707, 
    1.008319468, 0.980338613, 0.995596869, 0.995760716, 0.979296066, 
    1.040830214, 0.982629428, 0.98922114, 1.028132992, 1.047883065, 
    1.027944112, 1.058476395, 1.093980993, 1.098479613, 1.080672846, 
    1.095398052, 1.038954382, 1.059785386, 1.057663874, 1.055257511, 
    1.08289987, 1.069751139, 1.078103208, 1.063334474), Sex = structure(c(1L, 
    1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 
    1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 
    2L, 2L), levels = c("Female", "Male"), class = "factor"), 
    Group = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), levels = c("Control ", "Stress "
    ), class = "factor"), line_group = c("Female Stress ", "Female Stress ", 
    "Female Stress ", "Female Stress ", "Male Stress ", "Male Stress ", 
    "Male Stress ", "Male Stress ", "Female Stress ", "Female Stress ", 
    "Female Stress ", "Female Stress ", "Male Stress ", "Male Stress ", 
    "Male Stress ", "Female Control ", "Female Control ", "Female Control ", 
    "Female Control ", "Male Control ", "Male Control ", "Male Control ", 
    "Male Control ", "Female Control ", "Female Control ", "Female Control ", 
    "Female Control ", "Male Control ", "Male Control ", "Male Control ", 
    "Male Control ", "Female Stress ", "Female Stress ", "Female Stress ", 
    "Female Stress ", "Male Stress ", "Male Stress ", "Male Stress ", 
    "Male Stress ", "Female Stress ", "Female Stress ", "Female Stress ", 
    "Female Stress ", "Male Stress ", "Male Stress ", "Male Stress ", 
    "Female Control ", "Female Control ", "Female Control ", 
    "Female Control ", "Male Control ", "Male Control ", "Male Control ", 
    "Male Control ", "Female Control ", "Female Control ", "Female Control ", 
    "Female Control ", "Male Control ", "Male Control ", "Male Control ", 
    "Male Control ", "Female Stress ", "Female Stress ", "Female Stress ", 
    "Female Stress ", "Male Stress ", "Male Stress ", "Male Stress ", 
    "Male Stress ", "Female Stress ", "Female Stress ", "Female Stress ", 
    "Female Stress ", "Male Stress ", "Male Stress ", "Male Stress ", 
    "Female Control ", "Female Control ", "Female Control ", 
    "Female Control ", "Male Control ", "Male Control ", "Male Control ", 
    "Male Control ", "Female Control ", "Female Control ", "Female Control ", 
    "Female Control ", "Male Control ", "Male Control ", "Male Control ", 
    "Male Control ")), row.names = c(NA, -93L), class = c("tbl_df", 
"tbl", "data.frame"))

My code looks like this:

weight_gain_SI$Sex <- as.factor(weight_gain_SI$Sex)
weight_gain_SI$Group <- as.factor(weight_gain_SI$Group)
weight_gain_SI$Day <- as.factor(weight_gain_SI$Day)
weight_gain_SI$Rat <- as.factor(weight_gain_SI$Rat)

model  <- lm(Weight ~ Sex*Group*Day, data = weight_gain_SI,
         contrasts=list(Sex=contr.sum,Group=contr.sum, Day=contr.sum))

Anova(model, type=3)

When I run this code, I do not get the Mauchly’s test result and the Geisser – Greenhouse or Huynh – Feldt results. What code do I need to run in order to obtain these results?

I also tried to run this code:

new_anova <- Anova(model,
               idata=data.frame(Day),
               idesign = ~Day,
               type="III")
summary(new_anova, multivariate=FALSE)

but it gave me this output:

    Sum Sq               Df            F value             Pr(>F)         
 Min.   :  0.0005   Min.   :  1.00   Min.   :     0.2   Min.   :0.0000000  
 1st Qu.:  0.0458   1st Qu.:  1.00   1st Qu.:    28.4   1st Qu.:0.0000000  
 Median :  0.1033   Median :  9.00   Median :    99.1   Median :0.0000000  
 Mean   : 38.6102   Mean   : 34.44   Mean   :113348.9   Mean   :0.1247278  
 3rd Qu.:  0.2707   3rd Qu.:  9.00   3rd Qu.:   609.4   3rd Qu.:0.0000229  
 Max.   :346.0971   Max.   :270.00   Max.   :904371.0   Max.   :0.9977311  
                                     NA's   :1          NA's   :1

which is very different from the outputs I saw online that people obtained with that code. I would want an output that looks like this (screenshot from an online website, link: https://www.crumplab.com/rstatsforpsych/repeated-measures-anova.html):

output that someone else got with the same code

Can someone please help me with this issue? Many thanks in advance!

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Danh mục

How to get sphericity results with Anova() function from Car package