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...S01)) data <- na.omit(data1) In the following example, I am interested in the regression coefficient/semi-partial correlation of s1(x) and WSAS01 (y). Regression: m1 <- lm(WSAS01 ~ s1+s2+s3+s5+s10+age, data=data) summary(m1) regression coefficient s1: 0.091 Semipartial Correlation: library(ppcor) spcor.test(data$s1,data$WSAS01,data[,c("age","s2","s3","s5","s10")]) semi-partial correlation s1 with WSAS01: 0.202 What am I doing wrong? Thank you T [[alternative HTML version deleted]]

Dear fellow R-users I've always used Prof Harrell's rms package to calculate/visualize partial R2 values from a standard regression analysis (below is a quick example on how I've done so). Recently, I calcuated partial R2 values using the ppcor and gRbase packages. As it turns out, ppcor and gRbase agree with each other but the values generated from these packages tended to be greater than those generated by the rms package. Has anyone encountered a similar situation like mine? Yonghao ++++++++++++++++++++++++++++++++++++ f <- ols(...

...the covariate (standard length, SL), I need to use the partial correlation. I know how to calculate it with JMP, but as I used R to analyse all of my data (first time in my life) for this manuscript, can anyone help me to find a solution for this problem? I got some libraries to calculate it (e.g. ppcor, ggm, etc.), but none of them fit to my required analysis (fitting covariate and subset group) in the model. Any help will be very much appreciated. > ### Datafrmame> data1 <- read.csv(file.choose(),header=TRUE) #Partial correlation.csv> data1 Quantity Quality SL Irid.area Ca...

Hi, I want to know how i could calculate semi correlation with R. Is there any package for it? [[alternative HTML version deleted]]

Dear R users, In my data, there are two variables t1 and t2. For each observation of t1 and t2, two location indicators (x, y) were provided. The data format is # x y t1 t2 Since the both t1 and t2 are depended on x and y, t1 and t2 are autocorrelated variables. My question is how to calculate the correlation between t1 and t2 by taking into account the structure of residual variance

...ta mining. ? Is this likely to be a good approach? Or is there likely to be a better way of doing it? ? If it is a good approach, I?m wondering how to go about obtaining the necessary results. I?ve managed to figure out how to compute semi-partial correlations using the spcor.test() function in the ppcor package, as in: ? > spcor.test(as.numeric(Tested$TestStatus=="Yes"), Tested$predictor, Tested $nchar_record) ? ?? estimate????? p.value statistic?? n gp? Method 1 0.3853547 2.307562e-08? 5.587203 182? 1 pearson ? This is fine for a single pair of variables. What I?d need though is to c...