Multiple regression in R: Variable not found in data.frame - r

Question

Here's my data.frame :: beef
> head(beef)
YEAR....PBE CBE PPO CPO PFO DINC CFO RDINC RFP
1 1925 59.7 58.6 60.5 65.8 65.8 51.4 90.9 68.5 877
2 1926 59.7 59.4 63.3 63.3 68.0 52.6 92.1 69.6 899
3 1927 63 53.7 59.9 66.8 65.5 52.1 90.9 70.2 883
4 1928 71 48.1 56.3 69.9 64.8 52.7 90.9 71.9 884
5 1929 71 49.0 55.0 68.7 65.6 55.1 91.1 75.2 895
6 1930 74.2 48.2 59.6 66.1 62.4 48.8 90.7 68.3 874
And
dput(head(beef))
structure(list(YEAR....PBE = structure(1:6, .Label = c("1925 59.7",
"1926 59.7", "1927 63", "1928 71", "1929 71", "1930 74.2",
"1931 72.1", "1932 79", "1933 73.1", "1934 70.2",
"1935 82.2", "1936 68.4", "1937 73", "1938 70.2",
"1939 67.8", "1940 63.4", "1941 56"), class = "factor"),
CBE = c(58.6, 59.4, 53.7, 48.1, 49, 48.2), PPO = c(60.5,
63.3, 59.9, 56.3, 55, 59.6), CPO = c(65.8, 63.3, 66.8, 69.9,
68.7, 66.1), PFO = c(65.8, 68, 65.5, 64.8, 65.6, 62.4), DINC = c(51.4,
52.6, 52.1, 52.7, 55.1, 48.8), CFO = c(90.9, 92.1, 90.9,
90.9, 91.1, 90.7), RDINC = c(68.5, 69.6, 70.2, 71.9, 75.2,
68.3), RFP = c(877L, 899L, 883L, 884L, 895L, 874L)), .Names = c("YEAR....PBE",
"CBE", "PPO", "CPO", "PFO", "DINC", "CFO", "RDINC", "RFP"), row.names = c(NA,
6L), class = "data.frame")
I want to create a multiple linear regression model for PBE depending on the other variables. Following the tutorial in this link I think I should do something the following code:
> lm(formula = PBE ~ CBE + PBO + CPO + PFO +
+ DINC + CFO+RDINC+RFP+YEAR, data = beef)
Error in eval(expr, envir, enclos) : object 'PBE' not found
so I decided to try the followings but all have some errors:
> lm(formula=PBE~YEAR,data=beef)
Error in eval(expr, envir, enclos) : object 'PBE' not found
> lm(formula=beef$PBE~beef$YEAR)
Error in model.frame.default(formula = beef$PBE ~ beef$YEAR, drop.unused.levels = TRUE) :
invalid type (NULL) for variable 'beef$PBE
Can you please give me some insight where the typo/error is lying?
P.S.: I read the file using beef=read.table("beef.txt", header = TRUE, sep = "\t", comment.char="%") and the file looks like the following:
% http://lib.stat.cmu.edu/DASL/Datafiles/agecondat.html
%
% Datafile Name: Agricultural Economics Studies
% Datafile Subjects: Agriculture , Economics , Consumer
% Story Names: Agricultural Economics Studies
% Reference: F.B. Waugh, Graphic Analysis in Agricultural Economics,
% Agricultural Handbook No. 128, U.S. Department of Agriculture, 1957.
% Authorization: free use
% Description: Price and consumption per capita of beef and pork
% annually from 1925 to 1941 together with other variables relevant to
% an economic analysis of price and/or consumption of beef and pork
% over the period.
% Number of cases: 17
% Variable Names:
%
% PBE = Price of beef (cents/lb)
% CBE = Consumption of beef per capita (lbs)
% PPO = Price of pork (cents/lb)
% CPO = Consumption of pork per capita (lbs)
% PFO = Retail food price index (1947-1949 = 100)
% DINC = Disposable income per capita index (1947-1949 = 100)
% CFO = Food consumption per capita index (1947-1949 = 100)
% RDINC = Index of real disposable income per capita (1947-1949 = 100)
% RFP = Retail food price index adjusted by the CPI (1947-1949 = 100)
%
% The Data:
YEAR PBE CBE PPO CPO PFO DINC CFO RDINC RFP
1925 59.7 58.6 60.5 65.8 65.8 51.4 90.9 68.5 877
1926 59.7 59.4 63.3 63.3 68 52.6 92.1 69.6 899
1927 63 53.7 59.9 66.8 65.5 52.1 90.9 70.2 883
1928 71 48.1 56.3 69.9 64.8 52.7 90.9 71.9 884
1929 71 49 55 68.7 65.6 55.1 91.1 75.2 895
1930 74.2 48.2 59.6 66.1 62.4 48.8 90.7 68.3 874
1931 72.1 47.9 57 67.4 51.4 41.5 90 64 791
Here's the result of View(beef) as suggested by Patrick:

Answer 1

You need to go back and look at the file that you loaded these data into R from. The output from head() suggests that the first variable is YEAR....PBE and that the PBE data has gotten merged with the YEAR variable, probably because of some issue with the delimiters in use in the file you read in. Go back and check the file carefully.
One way to do this from within R is to use count.fields(), which you pass the filename to check. Do read ?count.fields as you will potentially need to set the sep and quote arguments in order to match the file you read the data from. The function will tell you how many fields (variables) it finds; compare this with the known number of variables.
From your edit, it is clear that something like what I describe above has happened:
> names(beef)
[1] "YEAR....PBE" "CBE" "PPO" "CPO" "PFO"
[6] "DINC" "CFO" "RDINC" "RFP"
It seems the file is not all/fully/truly Tab-delimited. I was able to read the bit of data you included with:
beef <- read.table("file.name", header = TRUE, sep = "", comment.char = "%")
> head(beef)
YEAR PBE CBE PPO CPO PFO DINC CFO RDINC RFP
1 1925 59.7 58.6 60.5 65.8 65.8 51.4 90.9 68.5 877
2 1926 59.7 59.4 63.3 63.3 68.0 52.6 92.1 69.6 899
3 1927 63.0 53.7 59.9 66.8 65.5 52.1 90.9 70.2 883
4 1928 71.0 48.1 56.3 69.9 64.8 52.7 90.9 71.9 884
5 1929 71.0 49.0 55.0 68.7 65.6 55.1 91.1 75.2 895
6 1930 74.2 48.2 59.6 66.1 62.4 48.8 90.7 68.3 874
> str(beef)
'data.frame': 7 obs. of 10 variables:
$ YEAR : int 1925 1926 1927 1928 1929 1930 1931
$ PBE : num 59.7 59.7 63 71 71 74.2 72.1
$ CBE : num 58.6 59.4 53.7 48.1 49 48.2 47.9
$ PPO : num 60.5 63.3 59.9 56.3 55 59.6 57
$ CPO : num 65.8 63.3 66.8 69.9 68.7 66.1 67.4
$ PFO : num 65.8 68 65.5 64.8 65.6 62.4 51.4
$ DINC : num 51.4 52.6 52.1 52.7 55.1 48.8 41.5
$ CFO : num 90.9 92.1 90.9 90.9 91.1 90.7 90
$ RDINC: num 68.5 69.6 70.2 71.9 75.2 68.3 64
$ RFP : int 877 899 883 884 895 874 791