Here are the implant stress results:
library(readxl)## Warning: package 'readxl' was built under R version 4.2.2a <- read_excel(file.choose(),sheet = "implant_von") # implant stress
library(MASS)
library(dplyr)## Warning: package 'dplyr' was built under R version 4.2.2##
## Attaching package: 'dplyr'## The following object is masked from 'package:MASS':
##
## select## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(tidyr)## Warning: package 'tidyr' was built under R version 4.2.2stress <- a$obs
mat <- a$material
t <- a$time
MA <- a$`muscle activation`
model <- aov(stress~mat+t+MA+mat:MA, data = a)
summary(model) # implant stress## Df Sum Sq Mean Sq F value Pr(>F)
## mat 1 214960373 214960373 264.540 <2e-16 ***
## t 1 136110645 136110645 167.504 <2e-16 ***
## MA 1 1946906 1946906 2.396 0.123
## mat:MA 1 1678219 1678219 2.065 0.152
## Residuals 181 147077308 812582
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Here are the brain MPS results:
brain_MPS <- read_excel(file.choose(),"Brain_MPS")
MPS <- brain_MPS$obs
cond <- brain_MPS$condition
ma1 <- brain_MPS$`muscle activation`
loc <- brain_MPS$location
t1 <- brain_MPS$time
model1 <- aov(MPS~cond*ma1*loc+t1, data = brain_MPS)
MPS_F <- brain_MPS %>% filter(location=="F")
MPS_p <- brain_MPS %>% filter(location=="P")
MPS_o <- brain_MPS %>% filter(location=="O")
fit1 <- aov(MPS_F$obs~MPS_F$condition*MPS_F$`muscle activation`+MPS_F$time, data = MPS_F)
fit2 <- aov(MPS_p$obs~MPS_p$condition*MPS_p$`muscle activation`+MPS_p$time, data = MPS_p)
fit3 <- aov(MPS_o$obs~MPS_o$condition*MPS_o$`muscle activation`+MPS_o$time, data = MPS_o)
summary(fit1)## Df Sum Sq Mean Sq F value
## MPS_F$condition 2 0.0000060 0.0000030 0.492
## MPS_F$`muscle activation` 1 0.0002635 0.0002635 43.106
## MPS_F$time 1 0.0005728 0.0005728 93.717
## MPS_F$condition:MPS_F$`muscle activation` 2 0.0000022 0.0000011 0.184
## Residuals 272 0.0016625 0.0000061
## Pr(>F)
## MPS_F$condition 0.612
## MPS_F$`muscle activation` 2.62e-10 ***
## MPS_F$time < 2e-16 ***
## MPS_F$condition:MPS_F$`muscle activation` 0.832
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit2)## Df Sum Sq Mean Sq F value
## MPS_p$condition 2 0.000194 0.0000971 2.969
## MPS_p$`muscle activation` 1 0.001403 0.0014029 42.909
## MPS_p$time 1 0.002928 0.0029277 89.550
## MPS_p$condition:MPS_p$`muscle activation` 2 0.000050 0.0000249 0.763
## Residuals 272 0.008893 0.0000327
## Pr(>F)
## MPS_p$condition 0.053 .
## MPS_p$`muscle activation` 2.86e-10 ***
## MPS_p$time < 2e-16 ***
## MPS_p$condition:MPS_p$`muscle activation` 0.467
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit3)## Df Sum Sq Mean Sq F value Pr(>F)
## MPS_o$condition 2 0.000486 0.000243 6.773 0.00135
## MPS_o$`muscle activation` 1 0.002696 0.002696 75.215 3.9e-16
## MPS_o$time 1 0.003854 0.003854 107.510 < 2e-16
## MPS_o$condition:MPS_o$`muscle activation` 2 0.000004 0.000002 0.062 0.94029
## Residuals 272 0.009751 0.000036
##
## MPS_o$condition **
## MPS_o$`muscle activation` ***
## MPS_o$time ***
## MPS_o$condition:MPS_o$`muscle activation`
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Here are the CSF shear strain results:
CSF_shear <- read_excel(file.choose(),sheet = "CSF_maxshear")
shear <- CSF_shear$obs
cond1 <- CSF_shear$condition
ma2 <- CSF_shear$`muscle activation`
loc1 <- CSF_shear$location
t2 <- CSF_shear$time
model2 <- aov(shear~cond1*ma2*loc1+t2, data = CSF_shear)
shear_F <- CSF_shear %>% filter(location=="F")
shear_p <- CSF_shear %>% filter(location=="P")
shear_o <- CSF_shear %>% filter(location=="O")
fit4 <- aov(shear_F$obs~shear_F$condition*shear_F$`muscle activation`+shear_F$time, data = shear_F)
fit5 <- aov(shear_p$obs~shear_p$condition*shear_p$`muscle activation`+shear_p$time, data = shear_p)
fit6 <- aov(shear_o$obs~shear_o$condition*shear_o$`muscle activation`+shear_o$time, data = shear_o)
summary(fit4)## Df Sum Sq Mean Sq F value
## shear_F$condition 2 0.0000059 0.0000029 0.374
## shear_F$`muscle activation` 1 0.0001102 0.0001102 14.049
## shear_F$time 1 0.0013312 0.0013312 169.761
## shear_F$condition:shear_F$`muscle activation` 2 0.0000221 0.0000110 1.409
## Residuals 272 0.0021330 0.0000078
## Pr(>F)
## shear_F$condition 0.688335
## shear_F$`muscle activation` 0.000218 ***
## shear_F$time < 2e-16 ***
## shear_F$condition:shear_F$`muscle activation` 0.246180
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit5)## Df Sum Sq Mean Sq F value
## shear_p$condition 2 0.000018 0.0000088 0.368
## shear_p$`muscle activation` 1 0.000879 0.0008794 36.754
## shear_p$time 1 0.002211 0.0022112 92.415
## shear_p$condition:shear_p$`muscle activation` 2 0.000038 0.0000188 0.785
## Residuals 272 0.006508 0.0000239
## Pr(>F)
## shear_p$condition 0.693
## shear_p$`muscle activation` 4.46e-09 ***
## shear_p$time < 2e-16 ***
## shear_p$condition:shear_p$`muscle activation` 0.457
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit6)## Df Sum Sq Mean Sq F value
## shear_o$condition 2 0.000003 0.0000017 0.082
## shear_o$`muscle activation` 1 0.001334 0.0013340 65.900
## shear_o$time 1 0.002823 0.0028226 139.436
## shear_o$condition:shear_o$`muscle activation` 2 0.000004 0.0000019 0.096
## Residuals 272 0.005506 0.0000202
## Pr(>F)
## shear_o$condition 0.921
## shear_o$`muscle activation` 1.66e-14 ***
## shear_o$time < 2e-16 ***
## shear_o$condition:shear_o$`muscle activation` 0.909
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Here are the disc stress results:
disc_von <- read_excel(file.choose(),"disc_von")
disc_stress <- disc_von$obs
cond2 <- disc_von$condition
ma3 <- disc_von$`muscle activation`
loc2 <- disc_von$location
t3 <- disc_von$time
model3 <- aov(disc_stress~cond2*ma3*loc2+t3, data = disc_von)
disc_1 <- disc_von %>% filter(location==1)
disc_2 <- disc_von %>% filter(location==2)
disc_3 <- disc_von %>% filter(location==3)
disc_4 <- disc_von %>% filter(location==4)
fit7 <- aov(disc_1$obs~disc_1$condition*disc_1$`muscle activation`+disc_1$time, data = disc_1)
fit8 <- aov(disc_2$obs~disc_2$condition*disc_2$`muscle activation`+disc_2$time, data = disc_2)
fit9 <- aov(disc_3$obs~disc_3$condition*disc_3$`muscle activation`+disc_3$time, data = disc_3)
fit10 <- aov(disc_4$obs~disc_4$condition*disc_4$`muscle activation`+disc_4$time, data = disc_4)
summary(fit7)## Df Sum Sq Mean Sq F value Pr(>F)
## disc_1$condition 2 0.155 0.077 1.780 0.171
## disc_1$`muscle activation` 1 0.000 0.000 0.005 0.945
## disc_1$time 1 11.982 11.982 275.179 <2e-16
## disc_1$condition:disc_1$`muscle activation` 2 0.127 0.063 1.455 0.235
## Residuals 272 11.844 0.044
##
## disc_1$condition
## disc_1$`muscle activation`
## disc_1$time ***
## disc_1$condition:disc_1$`muscle activation`
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit8)## Df Sum Sq Mean Sq F value Pr(>F)
## disc_2$condition 2 0.12 0.06 1.110 0.331
## disc_2$`muscle activation` 1 13.48 13.48 258.341 <2e-16
## disc_2$time 1 72.95 72.95 1397.699 <2e-16
## disc_2$condition:disc_2$`muscle activation` 2 0.23 0.11 2.162 0.117
## Residuals 272 14.20 0.05
##
## disc_2$condition
## disc_2$`muscle activation` ***
## disc_2$time ***
## disc_2$condition:disc_2$`muscle activation`
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit9)## Df Sum Sq Mean Sq F value Pr(>F)
## disc_3$condition 2 0.34 0.17 2.130 0.1208
## disc_3$`muscle activation` 1 76.90 76.90 975.019 <2e-16
## disc_3$time 1 242.09 242.09 3069.572 <2e-16
## disc_3$condition:disc_3$`muscle activation` 2 0.53 0.26 3.356 0.0363
## Residuals 272 21.45 0.08
##
## disc_3$condition
## disc_3$`muscle activation` ***
## disc_3$time ***
## disc_3$condition:disc_3$`muscle activation` *
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(fit10)## Df Sum Sq Mean Sq F value
## disc_4$condition 2 0.35 0.18 5.717
## disc_4$`muscle activation` 1 10.23 10.23 332.519
## disc_4$time 1 48.16 48.16 1565.906
## disc_4$condition:disc_4$`muscle activation` 2 0.49 0.24 7.939
## Residuals 272 8.37 0.03
## Pr(>F)
## disc_4$condition 0.003697 **
## disc_4$`muscle activation` < 2e-16 ***
## disc_4$time < 2e-16 ***
## disc_4$condition:disc_4$`muscle activation` 0.000446 ***
## Residuals
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1