# does linear regression adjusted t test adjust for individual values or just the mean?

I am trying to perform t-tests and ANOVAs on numerical parameters (eg. bone density) comparing groups. t-tests will be applied to a 2-group grouping method, and ANOVAs will be used when I hope to analyze in a 3-group manner. I want to adjust the parameter (bone density) taking another numerical parameter into consideration (eg. blood pressure). I have been able to compute the adjusted mean for the groups and p-values after adjustment. However, I am a little confused about whether I would be able to get the individual adjusted values. Is this linear regression process manipulating the mean or each individual value? I would greatly appreciate any input!

• Welcome to CV, brothy. It's impossible to know how to answer because you haven't told us how you computed "adjusted" values or what exactly you mean by "getting" the adjusted values. Maybe you could supply some details and/or a small example?
– whuber
Mar 14 at 22:58
• @whuber Thanks! I was using lm() function in R to obtain a linear regression adjusted value. Essentially through this line of code: summary(lm(df\$bonedensity ~ df\$TWOGROUP + df\$bloodpressure)). The two groups here are Control Participants and Diabetic Participants. R output intercept value as well as df\$TWOGROUP. I took the intercept value as the adjusted Control group mean, and intercept+df\\$TWOGROUP value as the Diabetic mean. Please let me know if I can elaborate further. I have also tried using the general linear model (univariant) with blood pressure as a covariant. Mar 15 at 0:25

cen <- function(x) {x - mean(x)}