# Re: st: RE: Complex Medical Data

 From TA Stat To statalist@hsphsun2.harvard.edu Subject Re: st: RE: Complex Medical Data Date Sun, 15 Feb 2009 13:50:30 +0700

```If reshape wide is used, that means "visit" is ignored.  However, but
both visit and drug are important in this case.  Look at each clinic
visit of John, he received GMMT at visit 1, visit 2 and visit 3, but
not visit 4.  GMMT can't be determined by one drug, but it is a
combination of some drugs.  In other words, I want to conclude that at
each visit, each patient received GMMT or not.

I can do Table 2 to Table 3, but not Table 1 to Table 2.

TA

On Sun, Feb 15, 2009 at 4:01 AM, Tom Trikalinos <ttrikalin@gmail.com> wrote:
> TA, see
>
> help reshape wide
>
> in reshaping, j will be your drug
>
> hth,
>
> TAT
>
>
> On Sat, Feb 14, 2009 at 12:22 AM, TA Stat <tastat@gmail.com> wrote:
>> For example, from table 1 to table 2, create a variable name "GMMT"
>> with the conditions explain earlier.  John received GMMT for visit 1,
>> visit 2, visit 4, but not visit 3.  Jen received GMMT at visit 1,
>> visit 2, visit 4, but not visit 3.
>>
>> Although at visit 4 for Jen, a combination of A4 and B3 is not GMMT,
>> but she also received C4. So she received GMMT.  At visit 3 for John,
>> he received C1 and D1 (any combination of drug from Class C and Class
>> D), so he received GMMT.
>>
>> I want to know how to get Table 2 from Table 1.
>>
>> ***************************************************************************************
>>
>> Table 1
>>
>> Name       Visit      Drug
>>
>> John           1           A1
>> John           1           B1
>> John           1           C1
>> John           2           A1
>> John           2           B1
>> John           3           C1
>> John           3           D1
>> John           4           B2
>> John           4           C2
>> John           4           D1
>> Jen             1           B3
>> Jen             1           C3
>> Jen             1           D4
>> Jen             2           A4
>> Jen             2           B3
>> Jen             2           C3
>> Jen             2           D4
>> Jen             3           A4
>> Jen             3           B3
>> Jen             4           A4
>> Jen             4           B3
>> Jen             4           C4
>>
>> ***************************************************************************************
>>
>> Table 2
>>
>> Name       Visit      Drug        GMMT (Y=Yes, N=No)
>>
>> John           1           A1            Y
>> John           1           B1            Y
>> John           1           C1            Y
>> John           2           A1            Y
>> John           2           B1            Y
>> John           3           C1            N
>> John           3           D1            N
>> John           4           B2            Y
>> John           4           C2            Y
>> John           4           D1            Y
>> Jen             1           B3            Y
>> Jen             1           C3            Y
>> Jen             1           D4            Y
>> Jen             2           A4            Y
>> Jen             2           B3            Y
>> Jen             2           C3            Y
>> Jen             2           D4            Y
>> Jen             3           A4            N
>> Jen             3           B3            N
>> Jen             4           A4            Y
>> Jen             4           B3            Y
>> Jen             4           C4            Y
>>
>>
>> ***************************************************************************************
>>
>> Table 3
>>
>> Name       Visit      Drug        GMMT (Y=Yes, N=No)
>>
>> John           1           A1            Y
>> John           2           A1            Y
>> John           3           C1            N
>> John           4           B2            Y
>> Jen             1           B3            Y
>> Jen             2           A4            Y
>> Jen             3           A4            N
>> Jen             4           A4            Y
>>
>>
>> On Sat, Feb 14, 2009 at 2:29 AM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>>> <>
>>>
>>> An example of data would help make this clearer.
>>>
>>> Nick
>>> n.j.cox@durham.ac.uk
>>>
>>> TA Stat
>>>
>>> I have data arranged in the format that each row represents one drug
>>> for clinic visit. So, one patient may have more than one drug (row)
>>> for each visit. Each patient also have several clinic visits.
>>>
>>> There are 4 classes of drugs, called Class A, Class B, Class C and
>>> Class D. Class A has four drugs, called A1, A2, A3 and A4. Class B has
>>> 3 drugs, called B1, B2, B3. so as Class C and Class D (as presented
>>> below). Some combination of drugs is called GMMT, other is not. I
>>> would like to find if each patient has received GMMT at each clinic
>>> visit or not. Basically, I want to identify whether patient receive
>>> GMMT for each visit or not.
>>>
>>> Class A: A1, A2, A3, A4
>>>
>>> Class B: B1, B2, B3
>>>
>>> Class C: C1, C2, C3
>>>
>>> Class D: D1, D2, D3, D4
>>>
>>> a combination of drug is called GMMT if
>>>
>>> Class A and Class B
>>>
>>> Class A and Class C
>>>
>>> Class A and Class D
>>>
>>> Class B and Class C
>>>
>>> Class A and Class B and Class C
>>>
>>> (However, there are some exception)
>>>
>>> but not for Class C and Class D
>>>
>>> but not for A4 and B3
>>>
>>>
>>> *
>>> *   For searches and help try:
>>> *   http://www.stata.com/help.cgi?search
>>> *   http://www.stata.com/support/statalist/faq
>>> *   http://www.ats.ucla.edu/stat/stata/
>>>
>> *
>> *   For searches and help try:
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>> *   http://www.stata.com/support/statalist/faq
>> *   http://www.ats.ucla.edu/stat/stata/
>>
> *
> *   For searches and help try:
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> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>
*
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```