R blank/NA ouput of ANOVA when comapring 2 GLMER function

See also questions close to this topic

• pivot_wider does not keep all the variables

  I would like to keep the variable cat (category) in the output of my function. However, I am not able to keep it. The idea is to apply a similar function to m <- 1 - (1 - se * p2)^df$n based on the category. But in order to perform that step, I need to keep the variable category.

  Here's the code:

  #script3
  
  suppressPackageStartupMessages({
    library(mc2d)
    library(tidyverse)
  })
  
  sim_one <- function() {
  df<-data.frame(id=c(1:30),cat=c(rep("a",12),rep("b",18)),month=c(1:6,1,6,4,1,5,2,3,2,5,4,6,3:6,4:6,1:5,5),n=rpois(30,5))
    nr <- nrow(df)
    df$n[df$n == "0"] <- 3
    se <- rbeta(nr, 96, 6)
    epi.a <- rpert(nr, min = 1.5, mode = 2, max = 3)
    p <- 0.2
    p2 <- epi.a*p
    m <- 1 - (1 - se * p2)^df$n
    results <- data.frame(month = df$month, m, df$cat)
    results %>%
      arrange(month) %>%
      group_by(month) %>%
      mutate(n = row_number(), .groups = "drop") %>%
      pivot_wider(
      id_cols = n,
      names_from = month,
      names_glue = "m_{.name}",
      values_from =m
      ) 
  }
  
  set.seed(99)
  
  iters <- 1000
  sim_list <- replicate(iters, sim_one(), simplify = FALSE)
  sim_list[[1]]
  #> # A tibble: 7 x 7
  #>       n    m_1    m_2    m_3    m_4   m_5    m_6
  #>   <int>  <dbl>  <dbl>  <dbl>  <dbl> <dbl>  <dbl>
  #> 1     1  0.970  0.623  0.905  0.998 0.929  0.980
  #> 2     2  0.912  0.892  0.736  0.830 0.890  0.862
  #> 3     3  0.795  0.932  0.553  0.958 0.931  0.798
  #> 4     4  0.950  0.892  0.732  0.649 0.777  0.743
  #> 5     5 NA     NA     NA      0.657 0.980  0.945
  #> 6     6 NA     NA     NA      0.976 0.836 NA    
  #> 7     7 NA     NA     NA     NA     0.740 NA
  

  ^{Created on 2022-05-07 by the reprex package (v2.0.1)}
• calculate weighted average over several columns with NA

  I have a data frame like this one:

  ID  duration1   duration2   total_duration  quantity1   quantity2
   1     5            2             7             3         1
   2     NA           4             4             3         4
   3     5            NA            5             2         NA
  

  I would like to do a weighted mean for each subject like this:

  df$weighted_mean<-  ((df$duration1*df$quantity1) + (df$duration2*df$quantity2) ) / (df$total_duration)
  

  But as I have NA, this command does not work and it is not very nice....

  The result would be this:

  ID  duration1   duration2   total_duration  quantity1   quantity2   weighted_mean
   1     5            2             7             3         1          2.43
   2     NA           4             4             3         4          4
   3     5            NA            5             2         NA         2
  

  Thanks in advance for the help
• I am to extract data from netCDF file using R for specific loaction the code i've written as showen and I have an error at the end of the code

  I need some help with extracting date from NetCDF files using R , I downloaded them from cordex (The Coordinated Regional climate Downscaling Experiment). In total I have some files. This files have dimensions of (longitude, latitude, time) and the variable is maximum temperature (tasmax). At specific location, I need to extract data of tasmax at different time. In total I have some files. This files have dimensions of (longitude, latitude, time) and variable maximum temperature (tasmax). At specific location, I need to extract data of tasmax at different time.I wrote the code using R but at the end of code, an error appeared. Error ( location subscript out of bounds)

  getwd() setwd("C:/Users/20120/climate change/rcp4.5/tasmax")

  dir()
  library ("ncdf4")
  libra,-ry(ncdf4.helpers)
  library ("chron")
  ncin <- nc_open("tasmax_AFR-44_ICHEC-EC-EARTH_rcp45_r1i1p1_KNMI-RACMO22T_v1_mon_200601-201012.nc")
  
  lat <- ncvar_get(ncin, "lat")
  
  lon <- ncvar_get(ncin, "lon")
  
  tori <- ncvar_get(ncin, "time")
  title <- ncatt_get(ncin,0,"title")
  institution <- ncatt_get(ncin,0,"institution") 
  datasource <- ncatt_get(ncin,0,"source") 
  references <- ncatt_get(ncin,0,"references")
  history <- ncatt_get(ncin,0,"history") 
  Conventions <- ncatt_get(ncin,0,"Conventions") 
  tustr <- strsplit(tunits$value,"")
  ncin$dim$time$units
  ncin$dim$time$calendar
  tas_time <- nc.get.time.series(ncin, v = "tasmax",
                             time.dim.name = "time")
  tas_time[c(1:3, length(tas_time) - 2:0)]
  tmp.array <- ncvar_get(ncin,"tasmax")
  dunits <- ncatt_get(ncin,"tasmax","units")
  tmp.array <- tmp.array-273.15
  tunits <- ncatt_get(ncin,"time","units")
  nc_close(ncin)
  which.min(abs(lat-28.9))
  which.min(abs(lon-30.2))
  tmp.slice <- tmp.array[126,32981,]
  tmp.slice
  

  Error in tmp.array[126, 32981, ] : subscript out of bounds
• How to save plots in a loop to different pdfs in R (for lmer plots)?

  in each itteration of a loop I want to save my plots into a pdf. I have found some good code examples (e.g. here), but for some reason it doesn´t work in my case. What have I been doing wrong?

  I did the following:

  save_as = "xxxx.pdf"
  
  # dataframe 
  Var1 <- c(1.0, 1.4, 2.0, 0.7, 0.8, 1.3, 1.6, 0.9, 0.5)
  Var2 <- c(100, 99, 320, 219, 280, 299, 210, 200, 190)
  Var3 <- c(10, 1, 4, 8, 19, 20, 7, 8, 2)
  indep1 <- c(10, 11, 14, 25, 23, 21, 33, 11, 14)
  indep2 <- c("species1", "species1", "species2", "species3", "species1", "species3", "species2", "species2", "species2")
  
  df <- data.frame(Var1, Var2, Var3, indep1, indep2)
  
  # dependent variables
  dep_vars = c("Var1", "Var2", "Var3")
  
  for (i in dep_vars){  
    ## model specification
    model1 = lmer(eval(parse(text=paste("df$", i, sep = ""))) ~ df$indep1 + (1|df$indep2))
    model2 = lmer(eval(parse(text=paste("df$", i, sep = ""))) ~ (1|df$indep2))
  
    # open pdf
    new_save_as = gsub('xxxx', i, save_as)
    pdf(new_save_as)
  
    # put plots in 
    par(mfrow = c(1,2))
  
    plot(model1, type=c("p", "smooth"), col.line=1)
    plot(model2, type=c("p", "smooth"), col.line=1)
    
    # close file
    dev.off()
  }
  

  If I run this without the loop, the file is created as I want it. But, if I use the loop the pdf is created but stays empty. Does anyone have an idea why?

  Also, any other comments on my code are welcome, as I am new to R.

  Thanks!
• Dealing with confounded effects in interactions, in R

  I am doing a regression analysis of hunting and wind power turbine data.

  My response variable is hunting harvest density, and a set of wind turbine variables: height, number of turbines, distance to turbines and establishment phase (pre-construction, construction and operative.

  examplemodel <- lme(harvest ~ WP_distance + WP_height + phase + phase:WP_distance + phase:WP_turbines, weight = ~ I(1/Area), data = mydata, random =~ 1 | randomvar, method="ML")

  In pre-construction phase, height, turbines and distance is set as zero (not built yet).

  When conducting linear mixed effects, i try to include the turbine variables and interactions phase:distance, phase:height, phase:turbines. However, when doing this i get error:

  Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1

  I figure it's because the variables phase and the wp-variables get confounded in this way, but how could i possibly deal with it otherwise? I want to display that the height, number of turbines and distance to the wind power parks depend on the construction phase.

  Thank you!