I am working with culture cells where one dish has been transfected with a scrambled knockdown clone and two dishes which have been transfected with two knockdown clones each knocking down the expression of a single gene. An example of an experiment I have performed is to measure the mitochondrial membrane potential (using a fluorescent … Read more
I'm in the process of running a repeated-measures ANOVA on two groups of participants from an experiment. In one group, there are 10 participants, and in the other group, there is only 1 participant. This is because the 1 participant is a patient who is being compared to the 10 other participants. Now, my question … Read more
While it's easy to compute the p-value of Krsukal-Wallis non-parametric test using the kruskal.test() function, I don't know how to compute the mean ranks and standard errors for each group. For instance suppose the following example: x <- data.frame(group=rep(1:2,each=10),height=runif(20)) kruskal.test(x$height, g=x$group) # Kruskal-Wallis rank sum test # data: x$height and x$group # Kruskal-Wallis chi-squared = … Read more
Let say I've ran this linear regression: lm_mtcars <- lm(mpg ~ wt + vs, mtcars) I can use anova() to see the amount of variance in the dependent variable accounted for by the two predictors: anova(lm_mtcars) Analysis of Variance Table Response: mpg Df Sum Sq Mean Sq F value Pr(>F) wt 1 847.73 847.73 109.7042 … Read more
I am running one-way ANOVA to determine whether several groups have differing means. I also run post-hoc multiple comparison to determine which means are different. The problem is that I need to have it showed which sets of groups are not different (like REGWQ test does). The problem is that Levene's test shows that the … Read more
I am running one-way ANOVA to determine whether several groups have differing means. I also run post-hoc multiple comparison to determine which means are different. The problem is that I need to have it showed which sets of groups are not different (like REGWQ test does). The problem is that Levene's test shows that the … Read more
I notice whenever I see an interaction plot for say a simple two factor ANOVA there are no error bars present, just the points for the estimated means. Is it ever appropriate to display error bars in an interaction plot for an ANOVA? If yes when would you want to do this and how would … Read more
I need to compare total concentrations of a chemical across different tissues of a plant species. I sampled multiple tissues from each individual, and sampled at multiple sites. I do not know how to handle the individual and site covariates. There is good reason to expect a site effect on chemical concentrations. I need to … Read more
If you choose to analyse a pre-post treatment-control design with a continuous dependent variable using a mixed ANOVA, there are various ways of quantifying the effect of being in the treatment group. The interaction effect is one main option. In general, I particularly like Cohen's d type measures (i.e., ${frac{mu_1 – mu_2}{sigma}}$). I don't like … Read more
I have a quick question about reporting simple main effects. I am running a two-way mixed ANOVA and the interaction effect was not significant. I understand that if you have no significant interaction effect, you should not carry out a test of simple main effects and instead just interpret the main effects. I really don't … Read more