Die ist aus dem Paket metafor.
Hier der Output mit str(data2) - ich hoffe, du kannst etwas damit anfangen.
Danke und viele Grüße!
> str(data2)
'data.frame': 51 obs. of 56 variables:
$ Whose.study : Factor w/ 3 levels "","A","F": 3 3 3 3 3 3 3 3 3 3 ...
$ Article_No : int 2 2 2 3 3 4 4 5 6 7 ...
$ Sample_No : int 2 2 2 3 3 4 5 6 7 8 ...
$ Effect_Size_No : int 2 3 4 5 6 7 8 9 10 11 ...
$ Reference... : Factor w/ 25 levels "","Banai, M., Stefanidis, A., Shetach, A., & ™zbek, M. F. (2014). \nAttitudes toward ethically questionable negotiation tactics: \"| __truncated__,..: 2 2 2 3 3 4 4 5 6 7 ...
$ Study.No. : Factor w/ 7 levels "","/","1","2",..: 1 1 1 1 1 3 4 1 1 3 ...
$ Year : int 2014 2014 2014 2016 2016 2010 2010 2011 2013 2009 ...
$ Continent.. : Factor w/ 10 levels "","America","America ",..: 6 6 6 5 5 2 2 9 2 2 ...
$ Country : Factor w/ 13 levels "","Brazil","Canada",..: 8 8 8 4 4 12 12 11 2 12 ...
$ MAS_Index : Factor w/ 11 levels "","42","45","47",..: 5 5 5 11 11 9 9 3 6 9 ...
$ Type_Of_Source.. : int 1 1 1 1 1 1 1 1 1 1 ...
$ Published.. : int 1 1 1 1 1 1 1 1 1 1 ...
$ N_Total : int 615 615 615 173 173 379 172 361 230 248 ...
$ Percentage_Women : Factor w/ 41 levels ""," 61.0 ","0.00%",..: 3 3 3 2 39 40 5 11 18 20 ...
$ N_WomenXXX : num 0 0 0 106 106 ...
$ N_Women : num 0 0 0 106 106 239 39 120 101 114 ...
$ N_Men : num 615 615 615 67 67 140 133 241 129 134 ...
$ Average_Age : Factor w/ 28 levels "","/","19.00",..: 2 2 2 2 2 3 13 25 26 9 ...
$ Kind_Of_Sample : Factor w/ 8 levels "","MBA","MBA\nWorking ",..: 8 8 8 7 7 7 2 8 8 7 ...
$ Behavior_Vs_Attitude : Factor w/ 3 levels "","attitude",..: 2 2 2 2 2 2 2 2 3 2 ...
$ Kind_Of_Negotiation : Factor w/ 5 levels "","face_to_face",..: 3 3 3 3 3 3 3 3 5 3 ...
$ Assessment_DV_UB... : Factor w/ 27 levels "","1","1 (two scales)",..: 8 8 8 27 27 27 27 21 16 3 ...
$ Variable_Characteristic : Factor w/ 3 levels "","binary","continuous": 3 3 3 3 3 3 3 3 1 3 ...
$ Context_Of_Neg : Factor w/ 11 levels "","/","/ ","Car_Selling",..: 2 2 2 2 2 2 2 2 8 2 ...
$ Score_Type...average..subscore : Factor w/ 4 levels "","/","average",..: 4 4 4 3 3 3 3 1 1 4 ...
$ Reliability_Of_Scale : Factor w/ 30 levels ""," .89",".57-.73",..: 15 6 7 23 24 27 21 18 30 8 ...
$ Kind_of_UB... : Factor w/ 5 levels "","/","Active",..: 2 2 2 2 2 2 2 2 2 2 ...
$ UB_Specified : Factor w/ 15 levels "","(A)","(A), False Pr.",..: 13 11 12 7 15 6 6 6 5 10 ...
$ Mean_Female : Factor w/ 33 levels "","-0.02","/",..: 28 26 16 25 25 22 21 1 1 1 ...
$ SD_Female : Factor w/ 29 levels ""," 1.25",".63",..: 16 20 2 10 11 4 3 1 1 1 ...
$ Mean_Men : Factor w/ 33 levels "","-0.05","/",..: 29 22 10 27 28 25 26 1 1 1 ...
$ SD_Men : Factor w/ 30 levels "",".75",".86",..: 17 20 22 9 8 3 2 1 1 1 ...
$ Mean_Gender : Factor w/ 12 levels "",".20",".27",..: 10 10 10 10 10 10 10 1 1 4 ...
$ SD_Gender : Factor w/ 9 levels "",".40",".43",..: 7 7 7 7 7 7 7 1 1 5 ...
$ Mean_UB : Factor w/ 16 levels "","-.36",".22",..: 4 4 4 4 4 4 4 1 1 12 ...
$ SD_UB : Factor w/ 15 levels "",".42",".95",..: 4 4 4 4 4 4 4 1 1 13 ...
$ Frequency_Use_UB : Factor w/ 7 levels "","/","M: 13/51 (25%)\nF: 5/45 (11%)",..: 2 2 2 2 2 2 2 1 1 2 ...
$ Direction_Gender_Coding : Factor w/ 5 levels "","/","female",..: 2 2 2 2 2 3 3 1 1 3 ...
$ Direction_Unethical_Behavior : int 1 1 1 1 1 1 1 1 1 1 ...
$ Correlation_Gender_UB : Factor w/ 16 levels "","-.02\n","-.03",..: 15 15 15 15 15 15 15 1 1 10 ...
$ Other_Values : Factor w/ 10 levels "","/","Chi-Quadrat (1, N=96)\n = 3.25, p=.07",..: 2 2 2 2 2 2 2 1 1 1 ...
$ Effect_Size : logi NA NA NA NA NA NA ...
$ Advocacy : Factor w/ 5 levels "","/","no","yes",..: 2 2 2 2 2 2 2 2 3 2 ...
$ Financial_Incentive : Factor w/ 4 levels "","/","no","yes": 2 2 2 2 2 2 2 2 3 2 ...
$ Type_Of_Negotiation : Factor w/ 4 levels "","/","distributive",..: 2 2 2 2 2 2 2 2 4 2 ...
$ Experience : Factor w/ 4 levels "","/","no","yes": 4 4 4 3 3 3 4 4 4 3 ...
$ Opponent_Sex : Factor w/ 3 levels "","/","no": 2 2 2 2 2 2 2 2 3 2 ...
$ Instruction_To_Maximize : Factor w/ 4 levels "","/","no","yes": 2 2 2 2 2 2 2 2 3 2 ...
$ Acquaintance : Factor w/ 3 levels "","/","no": 2 2 2 2 2 2 2 2 3 2 ...
$ Expectation_Future_Interaction : Factor w/ 4 levels "","/","no","yes": 2 2 2 2 2 2 2 2 4 2 ...
$ Gender_First_Author : Factor w/ 3 levels "","female","male": 3 3 3 2 2 2 2 3 2 2 ...
$ Explicit_Hypothesis_Gender_Differences: Factor w/ 3 levels "","no","yes": 2 2 2 3 3 2 2 2 2 2 ...
$ Steterotype_Activation : Factor w/ 3 levels "","/","no": 2 2 2 2 2 2 2 2 3 2 ...
$ Threat_Gender_Status : Factor w/ 3 levels "","/","no": 2 2 2 2 2 2 2 2 3 2 ...
$ Power_Differences : Factor w/ 4 levels "","/","no","yes": 2 2 2 2 2 2 2 2 3 2 ...
$ Mentioning_.Possibilty_UB : Factor w/ 4 levels "","/","no","yes": 2 2 2 2 2 2 2 2 3 2 ...