1. P

    Year as continous variable

    Hello, Im new in statistics. Can I use "years" as a continuos variable to see if NDVi (normalized difference vegetation index) has changed over the years positively or negatively, for example with a GLMM or GLm? Thanks!!!!
  2. R

    Survival analysis at few dates: glms? logrank? cox ?

    Hello, In many documentation I have read that Kaplan-Meier curves followed by logrank test and/or cox models are the most recommended statistical methods to analyse Survival and test for different factors that may impact the Survival. However, I have also heard that these are suitable if I...
  3. ybarnatan

    Which non-parametric test should I use while running GLM?

    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...
  4. R

    GLM for two quantitatives data as DV

    Hello all, I have the following data res=structure(list(Zone = 1:12, Cat1 = c(0.5, 3.5, 1, 1, 2, 5.75, 9.33333333333333, 9, 11.6666666666667, 3.41666666666667, 4.58333333333333, 0), Other_cat = c(48.5, 45.5, 42, 52, 50, 42.25, 39.6666666666667, 34, 41.3333333333333, 42.5833333333333...
  5. D

    Multiple A/B test in R: methodology and any know tutorial

    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...
  6. L

    Data frame of results

    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...
  7. L

    Adjust for overdispersion in glm family = binomial (logit) model

    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)...
  8. L

    Which model/test should I choose? (GLM..?)

    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...
  9. A

    Moran's I Spatial Autocorrelation. Interpreting results.

    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...
  10. R

    Help with R GLM Formula for paired/nested model

    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...
  11. W

    Link = log code won't work

    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...
  12. W

    General and generalised linear models

    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...
  13. S

    Approximating the probability of an event occuring from the output of a Poisson GLM

    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...
  14. V

    Am I interpreting this correctly?

    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...
  15. S

    Comparing fit of GLM to OLS regression

    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...
  16. V

    p-value for logistic regression

    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.
  17. R

    What GLM family if response is Bray-Curtis dissimilarity? Can I use adonis (vegan)?

    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...
  18. C

    Hypothesis difficulty

    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)}=...
  19. V

    Which Analysis is Correct? (if any)

    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...
  20. E


    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...