Hi everyone,

I am quite new in R and trying to find my way around, which worked well so far. My question might be also a bit statistical, but I hope I am still right here. I have a dataset of residues from different plots(Repetitions) on several days (DAA- 0-5) and would like to show whether there are statistical differences in residues from day to day. As I have collected samples from the same plots each day, I have tried to run an ANOVA with repeated measurements. I found two codes for doing this, which seem to be alright, but I struggle to perform a multiple paired t- test after the anova, to show where the day-to-day differences are.

My data:

```
Sample DAA Repetition Residues
<chr> <fct> <fct> <dbl>
1 Cyp SF DIL1000 Day 0-1 0 1 161.
2 Cyp SF DIL1000 Day 0-2 0 2 206.
3 Cyp SF DIL1000 Day 0-3 0 3 263.
4 Cyp SF DIL1000 Day 0-4 0 4 278.
5 Cyp SF DIL1000 Day 0-5 0 5 301.
6 Cyp SF DIL1000 Day 1-1 1 1 62.0
7 Cyp SF DIL1000 Day 1-2 1 2 115.
8 Cyp SF DIL1000 Day 1-3 1 3 98.6
9 Cyp SF DIL100 Day 1-4rep 1 4 75.2
10 Cyp SF DIL100 Day 1-5rep 1 5 80.9
# ... with 17 more rows
```

```
summary(Poll)
Sample DAA Repetition Residues
Length:27 0:5 1:6 Min. : 4.505
Class :character 1:5 2:5 1st Qu.: 16.443
Mode :character 2:5 3:6 Median : 25.079
3:5 4:6 Mean : 72.547
4:4 5:4 3rd Qu.: 89.786
5:3 Max. :300.541
>
```

The codes I have tried for the repeated measurements anovas:

```
within.aov <- anova_test(data = Poll, Residues ~ DAA, within = DAA, type = 3, white.adjust = TRUE)
```

Output:

```
Coefficient covariances computed by hccm()
> get_anova_table(within.aov)
ANOVA Table (type III tests)
Effect DFn DFd F p p<.05
1 DAA 5 21 42.518 2.75e-10 *
```

```
test<-aov(Residues~DAA+Error(Repetition/DAA), data=Poll)
summary(test)
```

output:

```
Error: Repetition
Df Sum Sq Mean Sq F value Pr(>F)
DAA 2 6130 3064.8 3.347 0.23
Residuals 2 1831 915.6
Error: Repetition:DAA
Df Sum Sq Mean Sq F value Pr(>F)
DAA 5 189056 37811 51.16 1.19e-09 ***
Residuals 17 12565 739
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
```

The t test I have tried:

```
pairwise.t.test(x=Poll$Residues, g=Poll$DAA, paired=T)
```

Which gave the following error:

```
> pairwise.t.test(x=Poll$Residues, g=Poll$DAA, paired=T)
Error in complete.cases(x, y) : arguments have not the same length
```

I assume that happens because I have less repetitions on DAA 4 and 5, but I am not sure how to solve this issue. Is there another test I could use?

Many thanks for any comments or tips, and I hope I have posted everything in the right format!