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 <https://www.youtube.com/redirect?q=http%3A%2F%2Foa.design%2F&redir_token=AaSAPDY-5UAsoHxN6BdwfyIJ7R98MTUzOTIxNDg2OUAxNTM5MTI4NDY5&event=comments>" 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 http://www.mediafire.com/file/39jlf9h539y9mdz/Homothetic+behaviour+investigation+on+fracture+toughness+of+asphalt+mixtures+using+semicircular+bending+test.pdf
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