Announcement

Collapse
No announcement yet.
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • Attaullah Shah
    replied
    Kiran Abro Sounds great that you have solved your problem. However, the error message that you have reported "
    File Myfile.doc already exists, option append was assumed)
    file Myfile.doc could not be opened for read/write"
    occurs when the file is open and you are trying to write to it. When you run asdoc and save to the same file which is currently open, it will not work. Either, you have to close the file or use a different file name using the option save(File_name).

    Leave a comment:


  • Kiran Abro
    replied
    issue resolved i just copied that table in another word doc and unsaved it from my.doc

    Leave a comment:


  • Kiran Abro
    replied
    this is very useful command. i was in search of this command and after days this post solved my problem. this is highly appreciated Professor Ataullah Shah. i just tried it for descriptive statistics and worked. then i tried it for correlation but stata issued an error message.

    (File Myfile.doc already exists, option append was assumed)
    file Myfile.doc could not be opened for read/write
    fopen(): 603 file could not be opened
    append(): - function returned error
    <istmt>: - function returned error
    r(603);

    Leave a comment:


  • Attaullah Shah
    replied
    Wawan Sugiyarto Today, I had some time so wrote this blog post to show the use of asdoc with ttest. The post uses your data. The output shown there is the standard output generated by asdoc with ttest command. If you need a more customized table, you can explore the row() option of asdoc, further details can be found in the help file of asdoc and in this blog post.

    Leave a comment:


  • Wawan Sugiyarto
    replied
    Dear Professor Shah,

    Thank you so much for your sharing. Your program is useful.

    I have problem with tabulate ttest ( Return=0) result in one table such as below (I input result manually one by one).

    ttest R0==0 if Y==2009
    ttest R1==0 if Y==2009
    ttest R2==0 if Y==2009
    ttest R3==0 if Y==2009

    ttest R0==0 if Y==2010
    ttest R1==0 if Y==2010
    ttest R2==0 if Y==2010
    ttest R3==0 if Y==2010

    ttest R0==0 if Y==2011
    ttest R1==0 if Y==2011
    ttest R2==0 if Y==2011
    ttest R3==0 if Y==2011

    ttest R0==0 if Y==2012
    ttest R1==0 if Y==2012
    ttest R2==0 if Y==2012
    ttest R3==0 if Y==2012

    Year Simulation Return (R)
    0 1 2 3
    2009 3 0.60 0.64 0.46 0.71
    (4.55) (3.72) (1.04) (3.26)
    2010 24 0.71 0.90 0.21 0.47
    (1.29) (1.64) (0.87) (2.67)
    2011 12 0.76 1.15 1.32 1.43
    (1.1) (1.77) (1.98) (1.84)
    2012 37 0.14 -0.13 -0.28 -0.26
    (0.74) (-0.63) (-1.04) (-0.99)
    Could you give some advices how to make it automatically?

    This is the dataset:
    R0 R1 R2 R3 Y
    0.004425 0.004425 -0.00405 0.003564 2009
    0.008808 0.010064 0.007259 0.006972 2009
    0.005156 0.005156 0.010822 0.011238 2009
    3.86E-05 -0.00165 -0.00303 -0.0049 2010
    0.009852 0.009852 -0.00301 -0.00524 2010
    0.0015 0.0015 -0.00666 -0.01387 2010
    -0.00061 -0.00045 -0.00055 0.000237 2010
    0.000747 0.000111 9.55E-05 0.001138 2010
    0.000771 -0.00015 -0.00031 0.003995 2010
    -0.00045 -0.00103 -0.00058 -0.00058 2010
    0.135216 0.135216 -0.00072 -0.00072 2010
    0.00053 0.000837 0.001047 -0.00249 2010
    0.001989 0.003614 0.001432 0.001534 2010
    0 0 0.008254 0.004437 2010
    -0.00266 -0.00559 -0.00494 -0.00229 2010
    0.005174 0.005418 0.015735 0.006711 2010
    0.004269 0.004468 0.004966 0.005369 2010
    0.008148 0.00438 -0.0419 0.005287 2010
    0.003946 0.007096 0.009817 0.015561 2010
    -0.00291 -0.00168 0.013342 0.019813 2010
    -0.00099 0.000613 0.003765 0.005096 2010
    -0.00095 -0.0005 0.007085 0.005976 2010
    0.003266 0.004288 0.007994 0.007191 2010
    0.006183 0.013831 -0.00515 0.003334 2010
    -0.00122 0.008168 0.008705 0.01362 2010
    -0.00036 0.011534 0.011966 0.017126 2010
    0.000918 0.0157 0.016885 0.021647 2010
    -0.01485 -0.01605 -0.01102 -0.00409 2011
    0.000353 0.002384 0.007114 0.017022 2011
    1.17E-05 -0.00186 0.009004 0.019676 2011
    -0.00164 0.000718 -5.2E-05 -0.00014 2011
    -3.51E-06 0.007894 0.003445 0.002757 2011
    -0.01009 0.016026 0.008748 -0.0063 2011
    -0.01611 -0.01043 -0.01148 -0.02287 2011
    0.003555 0.005695 0.011899 0.015045 2011
    0.011543 0.011453 0.013921 0.013737 2011
    0.022187 0.019799 0.020925 0.022505 2011
    0.018536 0.022491 0.019312 0.02012 2011
    0.059238 0.057683 0.063242 0.070793 2011
    0.008285 -3.1E-05 0.008224 0.00866 2012
    -0.00331 -0.0031 -0.00147 0.000799 2012
    -0.00205 -0.00235 0.003518 0.004122 2012
    0 0.003083 -0.0041 -0.00099 2012
    -0.01974 -0.02148 -0.02653 -0.0282 2012
    0.011725 0.002618 0.006607 0.004391 2012
    -0.01294 -0.02402 -0.02916 -0.02916 2012
    -0.00598 -0.01672 -0.03051 -0.03051 2012
    -0.0296 -0.03694 -0.05805 -0.05805 2012
    0.002149 -0.01434 -0.03187 -0.03187 2012
    -0.01341 -0.02352 -0.02146 -0.01403 2012
    0.011682 0.005818 -0.00138 0.004351 2012
    0.011756 0.011676 0.009072 0.006166 2012
    -0.00031 0.000313 -0.00034 -0.0019 2012
    0.000194 -0.00158 -0.00173 -0.00393 2012
    7.53E-05 -0.00208 -0.0017 -0.0035 2012
    0.000211 0.002246 0.001557 -0.00141 2012
    -0.00077 -0.00075 0.004118 0.000237 2012
    0.004429 0.004351 0.001652 0.001553 2012
    3.74E-05 -0.0042 -0.00712 0.000216 2012
    -0.00048 -0.00667 -0.00961 -0.00332 2012
    0.027808 0.029803 0.030471 0.026713 2012
    0.001292 -0.00982 -0.01935 -0.02156 2012
    0.034735 0.035506 0.036004 0.029923 2012
    -4E-05 0.000618 0.00168 0.004501 2012
    -0.00413 0.001406 0.003677 0.005576 2012
    -0.00017 -0.00331 -0.00124 0.002687 2012
    -0.00647 -0.00068 -0.00055 -0.00151 2012
    0.025387 -0.00014 0.000211 -0.00081 2012
    -0.00044 0.000535 -0.00017 0.001077 2012
    0.000138 0.000409 0.000608 0.003371 2012
    -0.01455 -0.00714 -0.00626 -0.00299 2012
    0.002515 0.005503 0.005963 0.005356 2012
    -0.00048 0.010277 0.013698 0.011827 2012
    0.022686 0.010046 0.009247 0.004038 2012
    0.011724 0.012328 0.006248 0.000934 2012
    0.001843 0.004669 0.011857 0.016241 2012

    Thank you.

    Kind regards,
    Wawan Sugiyarto

    Leave a comment:


  • Nick Cox
    replied
    EdieMMM Thanks for using your real name Eileen Díaz McConnell as signature.

    Back in #48 you said "I registered this account a long time ago, and I can't change my user name to my real name without setting up a new account". It is true that you can't do that unilaterally, but we explain what to do in your situation in the FAQ Advice which all are asked to read before posting.

    https://www.statalist.org/forums/help#realnames

    You are asked to post on Statalist using your full real name, including given name(s) and a family name, such as "Ronald Fisher" or "Gertrude M. Cox". Giving full names is one of the ways in which we show respect for others and is a long tradition on Statalist. It is also much easier to get to know people when real names are used.

    If you overlook this on first registration, it is easy to fix. Click on “Contact us” located at the bottom right-hand corner of every page.
    -- and send a message to the list administrators

    Leave a comment:


  • EdieMMM
    replied
    Professor Shah:

    Thanks so much for looking into this! I was on another project and just came back to check on this now. Yes, in the interest of providing a simple example, I didn't provide all that was needed. Sorry.

    However, I appreciate your taking the time to discover how to do this with another example. It worked perfectly!

    Also, running "asdoc mi estimate, append" also works so that I can just append rather than replace.

    Asdoc is such a time saver. Thank you.
    Eileen

    Leave a comment:


  • Attaullah Shah
    replied
    Thanks for the detailed example. However, you have not included many variables in the example dataset, but down the road, you do use them in the codes. Therefore, many commands fail. See, for example, this line of code
    Code:
    . mi register imputed IMMVALA_W23R ST7_W10R ST3_W10R ST8A_W10R ST8C_W10R ST8D_W10R
    variable ST3_W10R not found
    r(111);
    Similar is the case with some other variables. Given that, I shall use an example from the Stata manual for mi commands. Since you get an error message for the sub-command estimate, my example is based on this sub-command

    Code:
    webuse mheart1s20
    mi estimate: logit attack smokes age bmi hsgrad female
    
    * IF we use asdoc with the second line, we shall get an error: 
    
    asdoc mi estimate: logit attack smokes age bmi hsgrad female, replace
    
    variable estimate not found
    r(111);
    This happens due to parsing error at asdoc's end, which I shall work on in the subsequent updates. For time being, there is a good news. we can replay the mi estimates without having to repeat the full command. So if we type:

    Code:
     asdoc mi estimate, replace
    it does the trick and asdoc will export the mi estimates to a word file. So the solution is to first estimate the mi commands without using asdoc in the prefix, and then on the subsequent line, add asdoc to mi estimate, i.e.

    Code:
     mi estimate: logit attack smokes age bmi hsgrad female
    asdoc mi estimate, replace

    Leave a comment:


  • EdieMMM
    replied
    Hi again, Professor Shah.

    So this is a hypothetical example that doesn't include all my vars in my models and one of them isn't coded correctly (F_SEX_FINAL). But when I try the asdoc command that I cannot get to work, it shows the same error that I'm trying to show you, so I'm hoping this is enough to give you the key points without taking up too much of your time.



    Code:
    * Example generated by -dataex-. To install: ssc install dataex
    clear
    input byte(ST3scale_W10 ST8Ascale_W10 ST8Cscale_W10 ST8Dscale_W10 ST7_W10R IMMVALA_W23R REFUGEES_scale_W23) float ImmWorseScale_W10 byte Immdecrease_W10 double F_SEX_FINAL
    -1  0 -1  0 1 2 2  -.5 0 2
     1  1  1  0 3 4 0  .75 1 1
     0  1  1  1 3 4 0  .75 1 1
     1  0  1 -1 3 4 0  .25 1 2
    -1  0 -1  0 1 2 2  -.5 0 2
    -1  1  1  0 3 2 2  .25 1 1
    -1  1  1 -1 1 2 2    0 0 2
    -1  1 -1  0 3 2 2 -.25 1 2
     1  1  1  1 3 3 1    1 1 2
    -1  0 -1  0 1 1 3  -.5 0 2
    -1  0 -1 -1 3 2 2 -.75 1 2
     1  1  1  1 3 3 1    1 1 1
     1  1  1  1 3 4 0    1 1 1
     1  1  1  1 3 3 1    1 1 2
    -1 -1  0  1 1 2 2 -.25 0 1
    -1  0 -1 -1 1 3 1 -.75 0 1
    -1  0  0  0 1 2 2 -.25 0 1
    -1  1  1  0 3 2 2  .25 1 2
     1  1  1  1 2 3 1    1 0 2
    -1  1  0  0 1 1 3    0 0 1
     1  0  1  1 3 1 3  .75 1 2
    -1  0 -1  0 1 1 3  -.5 0 1
    -1 -1  1 -1 1 1 3  -.5 0 2
     1  1  1  0 3 2 2  .75 1 2
     1  1  1  1 3 2 2    1 1 1
    -1  0 -1 -1 1 2 2 -.75 0 2
     1  1  1  1 3 2 2    1 1 2
    -1  0  0  1 1 3 1    0 0 1
     1  0  1  0 3 2 2   .5 1 1
     1  1  1  1 3 3 1    1 1 2
     1  1  1  1 3 4 0    1 1 1
    -1  0 -1  0 1 2 2  -.5 0 1
    -1  0  0 -1 1 2 2  -.5 0 2
    -1  0 -1  0 1 1 3  -.5 0 2
     0  0 -1  0 1 3 1 -.25 0 1
     0  0 -1  0 1 3 1 -.25 0 1
    -1  0 -1  0 2 1 3  -.5 0 2
     . -1 -1 -1 1 1 3    . 0 2
    -1  0  0  0 2 2 2 -.25 0 2
     1  1  1  1 3 4 0    1 1 1
    -1  0 -1  0 1 1 3  -.5 0 1
    -1  1  1  1 3 2 2   .5 1 1
     1  1  1  1 3 4 0    1 1 2
    -1 -1 -1  0 1 4 0 -.75 0 1
    -1  0 -1  0 2 4 0  -.5 0 1
     0  1  1  0 1 3 1   .5 0 1
    -1  0  1  1 3 2 2  .25 1 2
    -1  0 -1  0 2 1 3  -.5 0 1
     1  1  1 -1 3 3 1   .5 1 1
    -1  0 -1  0 3 1 3  -.5 1 1
    -1  0  0  0 2 1 3 -.25 0 2
     1  1  1  0 3 3 1  .75 1 2
    -1  1  0  0 1 2 2    0 0 1
     1  1  1  0 3 4 0  .75 1 2
     .  1  1  1 3 2 2    . 1 2
    -1  0  0  0 2 1 3 -.25 0 2
     1  1  1  0 3 2 2  .75 1 2
     1  1  1  1 3 2 2    1 1 2
     1  1  0 -1 3 2 2  .25 1 2
    -1  0  0  0 2 1 3 -.25 0 2
     1  1  1  1 3 2 2    1 1 2
    -1  1  1 -1 3 3 1    0 1 2
    -1  0 -1  0 1 2 2  -.5 0 2
    -1  0 -1 -1 1 3 1 -.75 0 2
     1  1  1  1 3 3 1    1 1 2
    -1  1  1  0 3 2 2  .25 1 2
     0  0  0  0 1 1 3    0 0 2
     1  1  1  1 3 3 1    1 1 2
    -1  0  0  0 1 1 3 -.25 0 2
    -1  0 -1  0 2 2 2  -.5 0 1
     0  0  0  0 3 3 1    0 1 1
     1  1 -1  1 3 1 3   .5 1 2
     1  1  1  1 1 2 2    1 0 2
     1  0  1  0 3 2 2   .5 1 2
     0  0 -1  0 1 1 3 -.25 0 1
     1  1  1  0 3 3 1  .75 1 1
     0  1  0  0 1 1 3  .25 0 2
    -1  .  .  . . 1 3    . . 2
    -1  0 -1 -1 2 1 3 -.75 0 1
     1  1  1  1 2 3 1    1 0 2
    -1  1  0  0 1 1 3    0 0 2
     1  1  1  1 3 3 1    1 1 2
     1  1  1  1 3 3 1    1 1 2
    -1  0  0  0 1 1 3 -.25 0 2
    -1  0 -1 -1 3 2 2 -.75 1 2
     0  0 -1  0 2 2 2 -.25 0 2
    -1  0  0  0 1 . . -.25 0 2
    -1  0 -1  1 1 2 2 -.25 0 1
    -1  0 -1  0 2 1 3  -.5 0 2
    -1  0 -1 -1 2 1 3 -.75 0 1
    -1  1 -1 -1 2 2 2  -.5 0 1
    -1  0  1  0 1 4 0    0 0 2
     1  1  0  1 3 2 2  .75 1 1
    -1  0 -1  0 3 1 3  -.5 1 1
    -1  0 -1  0 1 1 3  -.5 0 2
     1  1  1  0 3 3 1  .75 1 2
    -1  0  0  0 1 2 2 -.25 0 2
     1  1  1  1 3 4 0    1 1 1
    -1  0 -1  0 2 1 3  -.5 0 1
     1  1  1  1 1 3 1    1 0 2
    end
    label values ST3scale_W10 ST3scale_W10
    label def ST3scale_W10 -1 "Make American society better in the long run", modify
    label def ST3scale_W10 0 "Don't have much of an effect", modify
    label def ST3scale_W10 1 "Make American society worse in the long run", modify
    label values ST8Ascale_W10 ST8Ascale_W10
    label def ST8Ascale_W10 -1 "Immigrants are making things better", modify
    label def ST8Ascale_W10 0 "Don't have much of an effect", modify
    label def ST8Ascale_W10 1 "Immigrants are making things worse", modify
    label values ST8Cscale_W10 ST8Cscale_W10
    label def ST8Cscale_W10 -1 "Immigrants are making things better", modify
    label def ST8Cscale_W10 0 "Don't have much of an effect", modify
    label def ST8Cscale_W10 1 "Immigrants are making things worse", modify
    label values ST8Dscale_W10 ST8Dscale_W10
    label def ST8Dscale_W10 -1 "Immigrants are making things better", modify
    label def ST8Dscale_W10 0 "Don't have much of an effect", modify
    label def ST8Dscale_W10 1 "Immigrants are making things worse", modify
    label values ST7_W10R ST7_W10R
    label def ST7_W10R 1 "Present level", modify
    label def ST7_W10R 2 "Increased", modify
    label def ST7_W10R 3 "Decreased", modify
    label values IMMVALA_W23R IMMVALA_W23R
    label def IMMVALA_W23R 1 "Very important goal", modify
    label def IMMVALA_W23R 2 "Somewhat important goal", modify
    label def IMMVALA_W23R 3 "Not too important goal", modify
    label def IMMVALA_W23R 4 "Not at all important goal", modify
    label values REFUGEES_scale_W23 REFUGEES_scale_W23
    label def REFUGEES_scale_W23 0 "Not at all important", modify
    label def REFUGEES_scale_W23 1 "Not too important", modify
    label def REFUGEES_scale_W23 2 "Somewhat important goal", modify
    label def REFUGEES_scale_W23 3 "Very important goal", modify
    label values Immdecrease_W10 Immdecrease_W10
    label def Immdecrease_W10 0 "No", modify
    label def Immdecrease_W10 1 "Decreased", modify
    label values F_SEX_FINAL F_SEX_FINAL
    label def F_SEX_FINAL 1 "Male", modify
    label def F_SEX_FINAL 2 "Female", modify
    *Below is code to give you idea of how I did the multiple imputation for the above data.

    mi extract 0, clear

    mi set mlong

    *This command identifies which variables in the imputation model don't have missing information, didn't include those that were subset of others.
    *I don't actually use this variable in the below syntax asdoc examples-but wasn't sure what would happen if I don't register any variables without missing data in this hypothetical example.

    mi register regular F_SEX_FINAL

    *This command identifies which variables in the imputation model has missing information.
    mi register imputed IMMVALA_W23R ST7_W10R ST3_W10R ST8A_W10R ST8C_W10R ST8D_W10R

    mi impute chained (ologit) IMMVALA_W23R (ologit) ST7_W10R (ologit) ST3_W10R (ologit) ST8A_W10R (ologit) ST8C_W10R (ologit) ST8D_W10R (ologit)[pweight = WEIGHT_W10], add(25) rseed (53421) augment force

    *After imputing the missing data, then I recode into what I need.

    *Recoded these imputed immigration attitudes into a mean scale.
    recode ST3_W10R (1 = -1 "Make American society better in the long run")(2 = 1 "Make American society worse in the long run")(3=0 "Don't have much of an effect"), gen(ST3scale_W10)

    recode ST8A_W10R (1 = -1 "Immigrants are making things better") (2 = 1 "Immigrants are making things worse") (3=0 "Don't have much of an effect"), gen(ST8Ascale_W10)

    recode ST8C_W10R (1 = -1 "Immigrants are making things better") (2 = 1 "Immigrants are making things worse") (3=0 "Don't have much of an effect"), gen(ST8Cscale_W10)

    recode ST8D_W10R (1 = -1 "Immigrants are making things better") (2 = 1 "Immigrants are making things worse") (3=0 "Don't have much of an effect"), gen(ST8Dscale_W10)

    *Mean scale for all 4 items: ImmWorseScale_W10 where higher values indicate more threat but also averaged across all 4.

    *Value ranges from -1 (all responses are immigrants make things better for all 4) to 1 (all responses are immigrants make things worse).
    gen ImmWorseScale_W10 = (ST3scale_W10 + ST8Ascale_W10 + ST8Cscale_W10 + ST8Dscale_W10)/ 4


    *ST7R to Binary, immigration should be decreased; those who think remain at present level or be increased increased are combined.
    recode ST7_W10R (1 = 0 "No")(2 = 0 "No")(3 = 1 "Decreased"), gen(Immdecrease_W10)


    *Continuous variable with very important as high and not at all important as low, I've checked it out-doesn't matter if lowest value is 1 or 0; regression results are the same with this var.

    recode IMMVALA_W23R (1 = 4 "Very important goal")(2 = 3 "Somewhat important goal")(3=2 "Not too important") (4=1 "Not at all important"), gen(REFUGEES_cont_W23)


    *The next command works fine for me.

    mi estimate: regress REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10

    *This next command works fine for me, too. Note that I shouldn't use logistic for this analysis given how REFUGEES_scale_W23 is coded, but it shows me that this asdoc mi estimate syntax works.

    asdoc mi estimate, or: logistic REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10

    *However, the next command-which is what I really want to run---produces an error ("variable estimate not found").

    asdoc mi estimate: regress REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10


    I hope that this runs for you, Professor Shah. If not, I will try again with another example.

    Thanks for the time that you've dedicated to asdoc and to advising users.

    Sincerely,
    Eileen Díaz McConnell

    Leave a comment:


  • EdieMMM
    replied
    There are a lot of them! I'll work on a short version to share and post again tomorrow. In the meantime, has anyone else using asdoc gotten this error with mi estimate: reg?

    Leave a comment:


  • Attaullah Shah
    replied
    I am not familiar with mi commands, so I am getting the following erorrs using your data
    Code:
    no imputations
    
    no imputations
    r(2000);
    Therefore, please post the relevant commands that you used to set the mi data and imputations.

    Leave a comment:


  • EdieMMM
    replied

    Hi again, Prof. Shah:

    I hope that this works!

    Code:
    * Example generated by -dataex-. To install: ssc install dataex
    clear
    input byte REFUGEES_scale_W23 float ImmWorseScale_W10 byte Immdecrease_W10
    2  -.5 0
    0  .75 1
    0  .75 1
    0  .25 1
    2  -.5 0
    2  .25 1
    2    0 0
    2 -.25 1
    1    1 1
    3  -.5 0
    2 -.75 1
    1    1 1
    0    1 1
    1    1 1
    2 -.25 0
    1 -.75 0
    2 -.25 0
    2  .25 1
    1    1 0
    3    0 0
    3  .75 1
    3  -.5 0
    3  -.5 0
    2  .75 1
    2    1 1
    2 -.75 0
    2    1 1
    1    0 0
    2   .5 1
    1    1 1
    0    1 1
    2  -.5 0
    2  -.5 0
    3  -.5 0
    1 -.25 0
    1 -.25 0
    3  -.5 0
    3    . 0
    2 -.25 0
    0    1 1
    3  -.5 0
    2   .5 1
    0    1 1
    0 -.75 0
    0  -.5 0
    1   .5 0
    2  .25 1
    3  -.5 0
    1   .5 1
    3  -.5 1
    3 -.25 0
    1  .75 1
    2    0 0
    0  .75 1
    2    . 1
    3 -.25 0
    2  .75 1
    2    1 1
    2  .25 1
    3 -.25 0
    2    1 1
    1    0 1
    2  -.5 0
    1 -.75 0
    1    1 1
    2  .25 1
    3    0 0
    1    1 1
    3 -.25 0
    2  -.5 0
    1    0 1
    3   .5 1
    2    1 0
    2   .5 1
    3 -.25 0
    1  .75 1
    3  .25 0
    3    . .
    3 -.75 0
    1    1 0
    3    0 0
    1    1 1
    1    1 1
    3 -.25 0
    2 -.75 1
    2 -.25 0
    . -.25 0
    2 -.25 0
    3  -.5 0
    3 -.75 0
    2  -.5 0
    0    0 0
    2  .75 1
    3  -.5 1
    3  -.5 0
    1  .75 1
    2 -.25 0
    0    1 1
    3  -.5 0
    1    1 0
    end
    label values REFUGEES_scale_W23 REFUGEES_scale_W23
    label def REFUGEES_scale_W23 0 "Not at all important", modify
    label def REFUGEES_scale_W23 1 "Not too important", modify
    label def REFUGEES_scale_W23 2 "Somewhat important goal", modify
    label def REFUGEES_scale_W23 3 "Very important goal", modify
    label values Immdecrease_W10 Immdecrease_W10
    label def Immdecrease_W10 0 "No", modify
    label def Immdecrease_W10 1 "Decreased", modify

    And, then:

    asdoc mi estimate: regress REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10

    I get this output:

    . asdoc mi estimate: regress REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10
    (File Myfile.doc already exists, option append was assumed)
    variable estimate not found
    r(111);

    So, I get the error.

    When I do this instead (even though its logistic with a continuous), I don't get the error.

    asdoc mi estimate, or: logistic REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10

    Output:
    . asdoc mi estimate, or: logistic REFUGEES_scale_W23 ImmWorseScale_W10 Immdecrease_W10
    (File Myfile.doc already exists, option append was assumed)


    Thanks for any suggestions!
    Eileen Diaz McConnell

    Leave a comment:


  • Attaullah Shah
    replied
    Eileen Diaz McConnell thanks for reporting this. Can you please post a data example using dataex (from SSC) and the exact command that you used

    Leave a comment:


  • EdieMMM
    replied
    --I registered this account a long time ago, and I can't change my user name to my real name without setting up a new account---


    Prof. Shah:

    This is a wonderful program! Thank you very much.


    I have been using it with imputed data and it works great with logistic regression.

    For example, this works perfectly with a binary DV....

    asdoc mi estimate, or: logistic DV IV IV IV, etc.


    However, I'm not getting it to work with the regression command with mi estimate and a continuous DV. This doesn't work for me:

    asdoc mi estimate: regress DV IV IV IV

    I get the error:

    variable estimate not found
    r(111);



    If I play around with it and try "asdoc regress DV IV IV IV" then it works. So, I think this might be a bug in asdoc with mi estimate: regress? Or am I supposed to be adding an option first? I have tried using asdoc mi estimate, coef: regress DV IV IV just to see but no luck.

    I have read through your website and searched statalist/google to see if others have reported this problem but haven't seen it mentioned...

    FYI, I am using Stata 14.2 and I have updated asdoc using:
    ssc install asdoc, replace
    Thanks in advance,
    Eileen Diaz McConnell

    Leave a comment:


  • Chen Samulsion
    replied
    Thank you professor Attaullah Shah. There are many user-written commands for exporting tables to text (word, excel, Latex) files in Stata, for example, estout, logout, outreg, outreg2, outtable, tabout, partchart, publish as far as I know. Some of them have obvious flaws, but also some have clear advantage. I hope someone can compare them with asdoc someday.

    Leave a comment:

Working...
X