[R] ANOVA in R

Thanh Tran m@@ternh@ttt @ending from gm@il@com
Wed Oct 10 01:47:06 CEST 2018

Hi eveyone,
I'm studying about variance (ANOVA) in R and have some questions to share.
I read an article investigating the effect of factors (temperature, Asphalt
content, Air voids, and sample thickness) on the hardness of asphalt
concrete in the tensile test (abbreviated as Kic). Each condition was
repeated four times (4 samples). In the paper, the authors used MINITAB to
analyze Anova. The authors use "adjusted sums of squares" calculate the
p-value I try to use ANOVA in R to analyze this data and get the result as
shown in Figure 4. The results are different from the results in the
article. Some papers say that in R, the default for ANOVA analysis is to
use "sequential sums of squares" to calculate the p-value.
So please help the following two questions: 1 / Introduction to code in R
for anova analysis uses "adjusted sums of squares". The main part of the
command in R / myself is as follows: > Tem = as.factor (temperature) > Ac =
as.factor (AC) > Av = as.factor (AV) > Thick = as.factor (Thickness) >
Twoway = lm (KIC ~ Tem + Ac + Av + Thick + Stamp + Ac + Stamp + Av + Stamp
+ Thick + Ac * Av + Ac * Thick + Av * Thick) > anova (twoway) 2/ When to
use "sequential sums of squares" and when to use "adjusted sums of
squares". Some papers recommend using the "oa.design
function in R to check for "orthogonal" designs. If not, use "adjusted sums
of squares". I am still vague about this command, so look forward to
everyone's suggestion. If you could answer all two of my questions, I would
be most grateful. Ps: I have added a CSV file and the paper for practicing
R. http://www.mediafire.com/file/e5oe54p2c2wd4bc/Saha+research.csv

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