I'm trying to analyze some experimental data about animal behaviour using R and would need some help or advice regarding which non-parametric test should I use.
The variables I have are:
- Response variable: "Vueltasmin", a numeric one
- Explicatory variable: "Condicion", a factor with 6 levels...
Dear All
I'm currently facing the following situation. We have run a marketing campaign providing to some members one of two type of coupones. In addition to this, some of these members were already contacted in the previous one by another campaign.
So I have the following dataset, where...
Hi all
Suppose I have 10 different models as such:
fit1.glm <- glm(admit ~ gre , data = dat, family = "binomial")
fit2.glm <- glm(admit ~ gpa, data = dat, family = "binomial")
fit3.glm <- glm(admit ~ rank, data = dat, family = "binomial")
...
Suppose then, I want to form a data frame...
I have an overdispersion problem in my model.. I have the following data:
y= succes/fail (%)
x= Var1 : Temperature data
m1<-glm(cbind(succes,fail)~Var1, data=data, family = binomial(logit))
Call:
glm(formula = cbind(succes, fail) ~ Var1, family = binomial(logit),
data = data)...
Hello!
I'm new to statistics but I am getting really stuck with my data so I hope someone could help me to choose the best statistical test. I have some test (dummy) data. I have data from 64 different hospitals, for 5 different countries countries, over 5 different years. In all of the...
I have carried out a Moran's I test on the residuals of a GLM model in the "ape" package in R which has returned the output below:
Observed: -0.158 Expected: -0.0303 SD: 0.058844 Probability: 0.030002
On this basis is it correct to state that there is negative spatial autocorrelation...
I have an experimental design as follows:
Two treatments, carried out on the same sample. The samples are collected from soil at five depths, in five different pits, from five different fields. I want to: (1) see if the treatment has an effect on the species richness found in the soil...
Hi,
doing a generalised linear model with poisson distribution, here is my model code...
model<-glm(carnivore_abundance~altitude_1+dist_stream+canopy_openess+basal_area+dist_large_river,family=poisson,data=main_data)
really frustratingly whenever I try to add link=log is doesn't work it...
Hi,
I've done a few GLM's with poisson distribution, the code I've used is
name<-glm(dependentvariable~independent+independent+independent,family=poisson,data=datset)
for some the dependent variable is non-normally distributed so I believe I need to use a generalised linear model. But...
Hi all,
I have some data that includes the output of a Poisson Log Link model, that aims to predict how many times an event will occur over the period of a year. I would like to approximate the probability of at least one event occurring from this output, though I am not sure how to go about...
I have a continuous DV and 2 categorical + 1 continuous IVs. In spss I did a univariate analysis and found a main effect of one of the categorical ivs and a significant interaction between the two categorical IVs and the DV. I am interested in seeing if there is a three way interaction between...
Hello talkstat.
First post in this magnificent forum!
In my master thesis I'm estimating health care expenses to patients, who has experienced a occupational injure on administrative data.
The depended variable is total health care expenses for a given individual a year after the...
How do I find the p-value for logistic regression. For example , for a glm output I :
z -value : 1.32 P ( > | Z | ) = 0.186696
If it were a normal regression would do : 2 ( 1 - P ( < | Z | ) = 2 (1-0.4066) = ???
The t-value = Estimate/ Std.Error...but P(>|t|) i don't understand.
I have some questions about testing for effects of different experimental levels on community similarity. I'll explain my planned experimental design before I ask the questions:
I have two methods for sampling species. I will use both of these methods on the same vegetation patch, at 3 points...
Let Y_{ij}=1 if the i^{\text{th}} child is classified as obese at the j^{\text{th}} occasion, and Y_{ij}=0 otherwise.
The marginal probability of obesity at each occasion follows the logistic model
log\frac{\Pr(Y_{ij}=1)}{\Pr(Y_{ij}=0)}=...
Hi! I have a design with two categorical iv and one continuous iv with a continuous dv. I wanted to see if there was a main effect or interaction from the categorical ivs, so I used the syntax:
glm DV by IV1 IV2.
There were no significant interactions or main effects. I wanted to then add...
Sorry for the wall of text, but I'm trying to figure out how to proceed and feel as though I need to clue you in as best I can.
Experimental Design:
Whole plot: Tree species (Spp) Subplot: Location relative to canopy boundary (In/Out)
Tests: 2-way ANOVA on data collected for several...
I have this data plotted as a scatter plot in Excel
I had done a regression in Excel, and the p value was 2.14E-05 while the R- value was 0.32. I was told the R value was too low compared to the significance of the p value, and was told to control for the dispersion of the data by running it...
Hi, I'm not very statistically minded but I would really appreciate some guidance. I am needing to do several stat tests for my MSc dissertation.
I have one dependent variable (species count) and one independent variable (year), but two species. I have constructed a basic count against year...