Multiple Chi Square Test on a factor with two levels and multiple parameters in a function-CodePudding

Issue

I have a group called Country that has two levels (Spain and Germany) and I have nine parameters that are measurements taken from spectrograms for dolphin whistles. I want to determine if any of the parameters are different between the countries.

For this analysis, I have been struggling with how to statistically compare both levels (Countries) within the group using a single Chi-Square test. Therefore, I did some research and this StackOverflow Post provides the answer that I need to use. However, they only use two parameters and they can insert a tilde - count~trap within their function to select them.

To solve this issue, I have produced a list of the nine parameters that I hoped to insert into the function in replacement (see R code 1). I like the output of R code 1 as it prints out the Chi-square p-value for both countries. However, I am struggling to figure out how to do this, and I've tried multiple combinations of R code, but I can't figure it out.

I got this error message for R code 1:

Error in formula.character(object, env = baseenv()) : 
  invalid formula c("Delta.Time", "Start.Freq", "End.Freq", "Low.Freq", "High.Freq", "Peak.Freq", "Delta.Freq", "Center.Freq", "Inflection.Points"): not a call
In addition: Warning message:
Using formula(x) is deprecated when x is a character vector of length > 1.
  Consider formula(paste(x, collapse = " ")) instead.

I tried a different method (see R Code 2) and this time I got loads of warning messages

Warning messages from R code 2

Warning messages:
1: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
2: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
3: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
4: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
5: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
6: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
7: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
8: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect
9: In chisq.test(table(x, Whistle_Parameters$Country)) :
  Chi-squared approximation may be incorrect

If anyone is able to help with how to insert the list called 'Outcomes' into the function in R code 1, I would be deeply appreciative.

Many thanks in advance.

R code 1

#List of acoustic parameters to conduct a Chi-square test
Outcomes<-c("Delta.Time", "Start.Freq","End.Freq", "Low.Freq", "High.Freq", 
            "Peak.Freq", "Delta.Freq", "Center.Freq", "Inflection.Points")

Country <- unique(Whistle_Parameters$Country)

chi_Country <- lapply(Country, function(x) xtabs(Outcomes, Whistle_Parameters[2:8], 
                                                 subset = Country == x))

chi_Country <- setNames(chi_Country, Country)

chi_Square_results<-lapply(chi_Country, chisq.test)

R-code 2

chi_Square_results<-lapply(Whistle_Parameters[,c("Delta.Time", "Start.Freq","End.Freq", "Low.Freq", "High.Freq", 
                             "Peak.Freq", "Delta.Freq", "Center.Freq", "Inflection.Points")], function (x) chisq.test(table(x, Whistle_Parameters$Country)))

chi_Square_results

Data - Whistle_Parameters

structure(list(Country = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("France", "Germany"
), class = "factor"), Low.Freq = c(1229.098358827, 759.408910773596, 
627.156561121131, 857.914227798394, 816.020512657709, 726.252107003186, 
603.388640229802, 1120.43591201848, 521.916239230762, 66.4277073927702, 
842.827028732445, 1548.00685289626, 743.586603639966, 982.298813187027, 
938.898554484786, 908.067281510105, 1650.51840217509, 435.837013213028, 
905.64518713548, 621.693057238002, 408.874626715846, 763.284854056395, 
1163.36397892984, 1267.90558781017, 1561.05494859439, 269.110242829792, 
1628.20258277437, 1381.52801863709, 1259.64885050619, 582.429604337893
), High.Freq = c(270.037998321385, 673.100410969792, 1354.51641087434, 
582.818682820139, 1949.42791374982, 533.072062804075, 1462.73353623344, 
1475.85981044777, 1672.72713391206, 1360.85064740235, 1027.62671423916, 
1637.72929840934, 555.708652550379, 683.537132648398, 1714.01010661954, 
267.117743854174, 738.883902818488, 842.919932827166, 124.511854388999, 
1940.70836004547, 991.37814311059, 1959.73951887933, 435.882938574683, 
223.944759894009, 827.050231552967, 1929.9835959516, 731.983627515309, 
934.515637669084, 1381.80407878684, 1735.12129509753), Start.Freq = c(209.223178720873, 
1243.93824398519, 714.942866646311, 1230.88587487336, 1133.38920481274, 
655.640254812419, 176.783487591076, 566.793710992312, 1259.4101411541, 
135.19626803044, 1188.65745695622, 1055.06564740433, 145.269654935287, 
994.102001940972, 611.97046714505, 1239.25416627405, 273.254811174704, 
1187.0983873612, 532.369927415851, 730.144132713145, 306.959091815357, 
761.432150933258, 833.35964575595, 633.492439842001, 1011.91529244509, 
1002.6837164403, 874.223664731894, 1039.77329580107, 571.716041690428, 
358.734914494325), End.Freq = c(3100.50977989246, 2865.99128764993, 
3749.07057886566, 1662.75251781181, 3469.5453928947, 1223.29004528624, 
1571.69393815622, 3877.90064918956, 3467.9046701139, 2812.46639335828, 
3344.48917919081, 823.479192696172, 3587.72640978872, 1943.42597579601, 
3726.46938122543, 904.270327650973, 2199.36865174236, 1608.75061469279, 
1233.86988042306, 3573.54022639883, 3840.13648049746, 2696.92512488242, 
2152.58952962537, 2225.74334558365, 2836.8576276391, 3909.86535579565, 
2642.3514330105, 3830.39875611625, 2532.59589574087, 2047.68204963624
), Peak.Freq = c(615.103200058515, 781.386010343022, 1254.22250479111, 
1042.32081012698, 1785.4136370848, 609.196990586287, 936.529532621528, 
628.617072934145, 1138.00887772997, 965.752651960148, 331.381776986669, 
831.243197072226, 1396.09323352817, 796.57855885715, 1434.02692184993, 
581.91826512844, 1482.84787412806, 712.229765737013, 711.849861782499, 
379.432018940052, 1495.87429192735, 1375.38825516007, 1568.51147252198, 
39.6849748542959, 254.973241980045, 526.048000326837, 1599.41223732841, 
1723.40465012645, 461.157566614546, 847.403323972557), Center.Freq = c(-0.00396318509300687, 
0.377462792184857, 1.66350671788962, -0.152573382048654, 0.438259482923988, 
1.62149800844459, 0.501892326424285, -0.166579179714419, 1.06081611813746, 
1.39199162769052, 1.52164843383928, -0.389958351497529, 0.00261034688899059, 
0.0726410215179534, 1.00473421813784, 1.27072495569536, 1.41569796343226, 
0.737375815997266, 0.412628778604207, 0.51099123600198, 1.65512836540775, 
-1.12408230668747, 0.438260531725931, -1.11347230908714, 1.09021071848368, 
1.26465014876586, -0.663254496003035, 0.64384027394782, 1.29816899903361, 
0.0302328674903059), Delta.Freq = c(2374.48934930825, 2535.28648042237, 
930.363518659463, 2372.94461226817, 2578.50041236941, 1652.93682378145, 
2412.64071270543, 1643.35808756239, 1597.6988634255, 2347.87731769764, 
1545.35983248752, 417.894712991398, 676.404759114593, 2717.74464723351, 
2750.52013318133, 1387.50061490775, 1088.18301844773, 208.885548316239, 
982.856603814324, 1304.55461743298, 2064.83914948351, 1454.17493801179, 
1975.72909682146, 1340.40119652782, 1358.81720189322, 398.974468430338, 
1807.83210129773, 197.995771350184, 1458.91300578134, 2459.54002342707
), Delta.Time = c(1.52332103330495, -0.729369599299347, 0.5446606158259, 
-0.0806278952890181, -1.03355982391612, 0.381391555011319, -0.710006011318096, 
0.184876103317229, -0.0939796220798944, 0.878826387745255, 0.889598364118577, 
0.929698941247702, 0.734996499853458, -0.43364546563554, -0.176575903721404, 
0.556057576098353, -0.31543237357059, 1.31950129257089, 1.08676447814548, 
-1.08756351145615, -0.163851619861579, -0.945982375537661, 0.473134073749239, 
-0.231569591521918, -0.565159893817776, 1.14721196081124, -1.14555651287826, 
1.60486934195338, -1.00704726744845, 1.14020903183312)), row.names = c(NA, 
30L), class = "data.frame")

CodePudding user response：

Not sure, why you want top subset for country. You can iteratively paste a formula together using sapply

sapply(Outcomes, \(x) xtabs(as.formula(paste(x, ' ~ Country')), Whistle_Parameters))
#         Low.Freq High.Freq Start.Freq End.Freq Peak.Freq Center.Freq Delta.Freq Delta.Time
# France   27190.8   32019.3   22677.68 79461.66  28306.01    16.81109   48043.22    4.67519
# Germany      0.0       0.0       0.00     0.00      0.00     0.00000       0.00    0.00000

CodePudding user response：

Thank you jay.sf for your answer, it was deeply appreciated

#List of acoustic parameters to conduct a Chi-square test
Outcomes<-c("Delta.Time", "Start.Freq","End.Freq", "Low.Freq", "High.Freq", 
            "Peak.Freq", "Delta.Freq", "Center.Freq", "Inflection.Points")

Country <- unique(Whistle_Parameters$Country)

chi_Country <- Chi_Squre_Results2<-sapply(Outcomes, \(x) xtabs(as.formula(paste(x, ' ~ Country')), Whistle_Parameters))

chi_Country <- setNames(chi_Country, Country)

chi_Square_results<-lapply(chi_Country, chisq.test)
chi_Square_results