[R] [NB] lm problems

[Matej Cepl]

Hi,

I have probably overlooked something obvious, but could anybody
help me with following, please?

Trying to make regression analysis. I have a huge dataframe with
results from National Opinion Survey on Crime and Justice
(www.abacon.com/fox/) with two variables G5 and N3 which are
imported to R as ordered factors:

	> levels(noscj$G5)
	[1] "Strongly agree"    "Agree"             "Neither"
	[4] "Disagree"          "Strongly disagree"
	> levels(noscj$N3)
	[1] "Serious problem"  "Somewhat problem" "Minor problem"  "Not
	a problem"
	>

(missing values are duly recoded as NA). When I try linear
regression I get a lot of warnings which I have not managed to
parse succesfully:

	> lm(G5 ~ N3,data=noscj)
	
	Call:
	lm(formula = G5 ~ N3, data = noscj)
	
	Coefficients:
	(Intercept)         N3.L         N3.Q         N3.C
	    3.38087     -0.05821     -0.15364      0.04367
	
	Warning message:
	"-" not meaningful for ordered factors in: Ops.ordered(y,
	z$residuals)
	> summary(lm(G5 ~ N3,data=noscj))
	
	Call:
	lm(formula = G5 ~ N3, data = noscj)
	
	Residuals:
	[1] <NA> <NA> <NA> <NA> <NA>
	Levels:  Strongly agree Agree Neither Disagree Strongly disagree
	
	Coefficients:
	            Estimate Std. Error t value Pr(>|t|)
	(Intercept)  3.38087
	N3.L        -0.05821
	N3.Q        -0.15364
	N3.C         0.04367
	
	Residual standard error: NA on 980 degrees of freedom
	Multiple R-Squared:    NA,      Adjusted R-squared:    NA
	F-statistic:    NA on 3 and 980 DF,  p-value: NA
	
	Warning messages:
	1: "-" not meaningful for ordered factors in: Ops.ordered(y,
	z$residuals)
	2: "^" not meaningful for ordered factors in: Ops.ordered(r, 2)
	3: ">" not meaningful for factors in: Ops.factor(qs[i], -Inf)
	4: "+" not meaningful for factors in: Ops.factor(qs[i],
	.minus(x[hi[i]], x[lo[i]]) * (index[i] - lo[i]))
	>

Could anybody tell me, what's going on, please? I have no clue
what "^", ">", etc. means.

	Thanks a lot (and thanks for your patience)

		Matej

-- 
Matej Cepl, matej at ceplovi.cz,
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