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Re: st: cascading dummies
From
Shikha Sinha <[email protected]>
To
[email protected]
Subject
Re: st: cascading dummies
Date
Mon, 1 Oct 2012 16:18:45 -0700
Richard,
You and also STB mentioned that coeff in regression using ordinal
dummies can be constructed by subtracting the coeff from the
regression using the standard dummies. Is this true for non-linear
regression as well (Logit, probit)? I could get it that way in an
ordinary least square but not sure about the non-linear regression.
Also, how do we interpret the coeff from cascading dummies?
lit | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
nfac1_12 | 1.674494 .0183205 47.12 0.000 1.638969 1.71079
nfac1_13 | 1.546588 .0202219 33.35 0.000 1.507457 1.586734
nfac1_14 | 1.397527 .0223861 20.90 0.000 1.354332 1.442099
nfac1_15 | 1.579932 .0347163 20.82 0.000 1.513334 1.649462
Does the odds ratios of 1.397527 mean that an increase in the dummy
from 3 to 4 results in 39% increase in literacy?
Thanks,
Shikha
On Mon, Oct 1, 2012 at 12:15 PM, Nick Cox <[email protected]> wrote:
> As Richard said, Stata can tell you:
>
> . findit cascade
>
> STB-6 srd11 . . . . . . . . . Generating ordered "cascading" dummy variables
> (help cascade if installed) . . . . . . . . . . . . . . . R. Goldstein
> 3/92 pp.19--22; STB Reprints Vol 1, pp.190--194
> add a set of new dummy variables that are cascading; that is,
> 0/1 variables are created where a 1 is given if the case has
> the value <= value of lowest category
>
> Accessible at http://www.stata.com/products/stb/journals/stb6.pdf
>
> Nick
>
> On Mon, Oct 1, 2012 at 7:59 PM, Shikha Sinha <[email protected]> wrote:
>> Thanks Richard!
>>
>> very helpful. What is the full reference of STB article, I am unable to find it.
>
> On Mon, Oct 1, 2012 at 11:39 AM, Richard Goldstein
>> <[email protected]> wrote:
>
>>> neither is wrong or right -- they answer slightly different questions; A
>>> asks for each dummy whether, and by how, much it is different from the
>>> reference group (you do realize that you should only include 4 of the
>>> dummies, right?); B asks whether each differs from the preceding level
>>>
>>> you can -findit cascade- to find a program I wrote to implement
>>> cascading dummies; the help file, and even more the STB article,
>>> discusses the differences; note that you can obtain the answer to either
>>> question by following up the original method of forming the variables
>>> with the appropriate -test- command(s)
>
> On 10/1/12 2:31 PM, Shikha Sinha wrote:
>
>>>> Recently, I came across a new way of creating dummies and I wonder
>>>> what the group thinks about this form.
>>>>
>>>> The independent variable X is coded as 1- very poor, and 5 as very
>>>> rich. I want to estimate the effect by wealth quintile. I created the
>>>> dummy the following ways, but I was told that this is wrong (A is
>>>> wrong). The correct way to construct dummy is B and is called
>>>> cascading dummies. I have never come across this before and would
>>>> appreciate if you could shed light on the difference between the two
>>>> and which is the correct way of creating dummies.
>>>>
>>>> A:
>>>> id Y X1 (scale of 1-5), dum1 dum2 dum3 dum4 dum5
>>>> 1 100 5 0 0 0 0 1
>>>> 2 200 4 0 0 0 1 0
>>>> 3 300 3 0 0 1 0 0
>>>> 4 239 2 0 1 0 0 0
>>>> 5 345 1 1 0 0 0 0
>>>>
>>>>
>>>> B:
>>>> id Y X1 (scale of 1-5), dum1 dum2 dum3 dum4 dum5
>>>> 1 100 5 1 1 1 1 1
>>>> 2 200 4 1 1 1 1 0
>>>> 3 300 3 1 1 1 0 0
>>>> 4 239 2 1 1 0 0 0
>>>> 5 345 1 1 0 0 0 0
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