[R] Getting INDIVIDUAL effects of multiple qualitative variables (ordered and unordered factors)

[Richard M. Heiberger]

## I think this is what you are looking for.
## Your download host seems to want to give me software, so I am not taking it.

tmp <- data.frame(y=rnorm(20), a=factor(rep(letters[1:4], each=5)))

tmp.aov <- aov(y ~ a, data=tmp)

summary(tmp.aov)

summary(tmp.aov, split=list(a=list(b=1, c=2, d=3)))

summary.lm(tmp.aov)

Rich

On Thu, May 7, 2015 at 2:43 PM, Rafael Costa
<rafaelcarneirocosta.rc at gmail.com> wrote:
> Dear R users,
>
> I have data from a questionnaire and I want to estimate the individual
> effect of each explanatory variable (all are qualitative) on the dependent
> variable (continuous). However, the default is to consider the estimated
> coefficients as the difference between the reference group (estimated value
> of the intercept) and the coefficient of the group. Each qualitative
> variable relates to a characteristic of a particular activity and the
> continuous variable is the time taken to perform this activity. I emphasize
> that the reference level of each factor relates to the case where none of
> the options for that factor was marked. The data is in "
> http://www.datafilehost.com/d/c7f0d342". I did not put them in the script,
> because I still do not know how to do this, but I hope this is not a
> problem (and I ask my sincere apologies). I do not put just a sample of the
> data, since there was singular matrix problems.
>
>
>
> First (and main) issue - In order to obtain the individual effect of the
> levels of each factor, I considered that the reference group has zero
> effect and I did the following steps:
>
>
>
> # Since the file was not loaded in the script, it is assumed here that it
> was downloaded from the internet and is already loaded in R.
>
> # I will make a quantile regression, so the package follows.
>
> install.packages (quantreg)
>
> library (quantreg)
>
> # Transforming factors into individual objects:
>
> p_1 = table (1: length (tabela1.1 $ p1), as.factor (tabela1.1 $ p1))
>
> p_21 = table (1: length (tabela1.1 $ p21), as.factor (tabela1.1 $ p21))
>
> p_22 = table (1: length (tabela1.1 $ p22), as.factor (tabela1.1 $ p22))
>
> p_23 = table (1: length (tabela1.1 $ p23), as.factor (tabela1.1 $ p23))
>
> p_24 = table (1: length (tabela1.1 $ p24), as.factor (tabela1.1 $ p24))
>
> p_25 = table (1: length (tabela1.1 $ p25), as.factor (tabela1.1 $ p25))
>
> p_34 = table (1: length (tabela1.1 $ p34), as.ordered (tabela1.1 $ p34))
>
> p_5 = table (1: length (tabela1.1 $ p5), as.ordered (tabela1.1 $ p5))
>
> p_6 = table (1: length (tabela1.1 $ p6), as.ordered (tabela1.1 $ p6))
>
> p_7 = table (1: length (tabela1.1 $ p7), as.ordered (tabela1.1 $ p7))
>
> p_8 = table (1: length (tabela1.1 $ p8), as.ordered (tabela1.1 $ p8))
>
> p_9 = table (1: length (tabela1.1 $ p9), as.ordered (tabela1.1 $ p9))
>
> # Regressing the model without intercept, but considering that the
> reference group = 0, considering that the reference group means that none
> of the factors has been marked (if any was marked, I believe that the time
> taken to perform the activity is practically zero).
>
> qrModel=rq(data=tabela1.1, pontoefetivo ~ 0 + p_1[,-1] + p_21[,-1] +
> p_22[,-1] + p_23[,-1] + p_24[,-1] + p_25[,-1] + p_34[,-1] + p_5[,-1] +
> p_6[,-1] + p_7[,-1] + p_8[,-1] + p_9[,-1], tau=0.5)
>
> summary(qrModel)
>
> My idea was that since the effect of the reference group is zero, the
> estimated coefficient of each level is precisely the individual effect of
> the chosen variable level. My idea is right? If not, what do I do to get
> these individual effects?
>
>
>
> Problem 2 - Assuming all is right above, ordered factors not have
> increasing effects [See summary (qrModel)]. But should not they have? If
> so, what do I do to ensure such an effect?
>
>
>
> Problem 3 - Again assuming that everything is correct, I hope that any
> estimated coefficients (individual effects on the runtime of the activity)
> are not negative values. Am I right about that? If so, what do I do to
> ensure that all values are not negative?
>
>
> I am looking forward  any help.
>
> Thanks in advance ,
>
> Rafael Costa.
>
>         [[alternative HTML version deleted]]
>
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