DATA Step, Macro, Functions and more

multiple imputation

Reply
Contributor
Posts: 43

multiple imputation

[ Edited ]

The following is the code I imputed and the log. And the attached is the original data I used.  I want to use quarter data to impute weekly data but there is something wrong. I refer to "Multiple Imputation for Missing Data: Concepts and News Development". The attached is the data which has more information because it starts in 2008 quarterly, and I don't know whether it will be useful for monotone or not.

input date	search_volume	open_price	volume	mood_prive	mood_economic	mood_government	mood_investment	mood_global	mood_possibility
;
informat date yymmdd.;
format date yymmdd10.;
datalines;
2013-12-29	31265.96873	8585.37	8868976	.	.	.	.	.	.
2014-01-05	27950.70473	8553	25542285	.	.	.	.	.	.
2014-01-12	25902.91541	8587.49	23798004	.	.	.	.	.	.
2014-01-19	23850.62263	8595.59	21013310	.	.	.	.	.	.
2014-01-26	16471.45342	8519.48	4003706	102.6	86.4	108.3	94.6	117.5	113.7
2014-02-02	18413.8849	8290.17	13577988	.	.	.	.	.	.
2014-02-09	22096.8015	8416.42	20932955	.	.	.	.	.	.
2014-02-16	21174.52948	8537.83	20897446	.	.	.	.	.	.
2014-02-23	19110.34379	8603.61	18451389	.	.	.	.	.	.
2014-03-02	20039.02689	8627.15	23866751	.	.	.	.	.	.
2014-03-09	20082.52542	8706.43	21628830	.	.	.	.	.	.
2014-03-16	18755.35847	8697.26	22388151	.	.	.	.	.	.
2014-03-23	18181.1214	8540.27	22001681	.	.	.	.	.	.
2014-03-30	16583.05049	8802.93	18635131	.	.	.	.	.	.
2014-04-06	17277.2075	8844.91	23653011	.	.	.	.	.	.
2014-04-13	16706.70072	8897.23	21848387	.	.	.	.	.	.
2014-04-20	16448.80356	8961.52	25353783	.	.	.	.	.	.
2014-04-27	15159.39418	8680.14	19053126	.	.	.	.	.	.
2014-05-04	16407.68482	8895.87	24751657	.	.	.	.	.	.
2014-05-11	15863.96562	8893.72	21302355	.	.	.	.	.	.
2014-05-18	14733.00752	8901.54	21286694	.	.	.	.	.	.
2014-05-25	14988.46355	9040.49	25196797	100.6	84.7	94.2	93.5	117.6	117.4
2014-06-01	13836.44918	9106.61	21298265	.	.	.	.	.	.
2014-06-08	14721.77203	9153.93	25439138	.	.	.	.	.	.
2014-06-15	14364.49877	9196.23	25290129	.	.	.	.	.	.
2014-06-22	14247.61966	9293.06	24519615	.	.	.	.	.	.
2014-06-29	13867.25553	9332.44	31407426	.	.	.	.	.	.
2014-07-06	13952.17408	9497.27	31082280	.	.	.	.	.	.
2014-07-13	13606.93546	9497.81	30163910	.	.	.	.	.	.
2014-07-20	12365.85288	9453.78	22175631	.	.	.	.	.	.
2014-07-27	13382.69317	9415.9	31581958	.	.	.	.	.	.
2014-08-03	13215.86645	9280.29	28543120	.	.	.	.	.	.
2014-08-10	12929.63734	9109.83	26019178	.	.	.	.	.	.
2014-08-17	12262.72744	9222.73	26300484	106	95.6	101.7	99.6	110.8	118.2
2014-08-24	11969.15285	9393.24	28277607	.	.	.	.	.	.
2014-08-31	12274.05186	9474.41	24938544	.	.	.	.	.	.
2014-09-07	11168.15524	9452.14	18875091	.	.	.	.	.	.
2014-09-14	10709.79633	9206.41	22890528	.	.	.	.	.	.
2014-09-21	10817.08069	9220.54	25272005	.	.	.	.	.	.
2014-09-28	10663.75135	9018.46	25827744	.	.	.	.	.	.
2014-10-05	9763.12662	9118.28	18627350	.	.	.	.	.	.
2014-10-12	10960.82462	8767.42	29734551	.	.	.	.	.	.
2014-10-19	9997.050868	8617.08	23795287	91	79.5	94.5	87.1	99.7	105.1
2014-10-26	9944.235397	8671.51	26800560	.	.	.	.	.	.
2014-11-02	9784.14586	9009.38	26105437	.	.	.	.	.	.
2014-11-09	9546.99488	8937.59	26419817	.	.	.	.	.	.
2014-11-16	9244.900155	9003.37	26437142	.	.	.	.	.	.
2014-11-23	8808.63662	9144.42	24429230	.	.	.	.	.	.
2014-11-30	9175.051622	9038.41	30591366	.	.	.	.	.	.
2014-12-07	9101.637737	9231.24	26818238	.	.	.	.	.	.
2014-12-14	9172.5426	8987.95	27376696	.	.	.	.	.	.
2014-12-21	9123.711552	9032.42	28035931	.	.	.	.	.	.
2014-12-28	7537.97184	9216.43	12659602	.	.	.	.	.	.
2015-01-04	8631.193364	9292.31	28375399	.	.	.	.	.	.
2015-01-11	8838.39816	9198.02	27159441	.	.	.	.	.	.
2015-01-18	9033.024336	9183.76	28166155	.	.	.	.	.	.
2015-01-25	8806.864325	9474.56	24158921	107.4	104.3	100.1	103	106.3	112.9
2015-02-01	8292.73749	9368.83	22232706	.	.	.	.	.	.
2015-02-08	8117.578392	9465.12	19033502	.	.	.	.	.	.
2015-02-22	6591.595891	9582.39	13351786	.	.	.	.	.	.
2015-03-01	7429.726695	9665.11	22863592	.	.	.	.	.	.
2015-03-08	8641.626314	9617.04	24552198	.	.	.	.	.	.
2015-03-15	8644.147128	9583.45	26949243	.	.	.	.	.	.
2015-03-22	8632.189365	9759.88	26912945	.	.	.	.	.	.
2015-03-29	8322.389316	9533.38	19524422	.	.	.	.	.	.
2015-04-05	7574.663565	9619.97	19816370	.	.	.	.	.	.
2015-04-12	7734.082764	9622.64	26447471	.	.	.	.	.	.
2015-04-19	8239.993245	9541.83	31624373	.	.	.	.	.	.
2015-04-26	7965.947754	9941.18	24944950	103.7	97.8	102.2	100.5	115.8	118.6
2015-05-03	7611.97648	9853.51	27094159	.	.	.	.	.	.
2015-05-10	7948.371142	9763.94	27128808	.	.	.	.	.	.
2015-05-17	8049.740643	9603.75	28939396	.	.	.	.	.	.
2015-05-24	7569.963872	9654.28	28573397	.	.	.	.	.	.
2015-05-31	7514.023004	9688.13	30180031	.	.	.	.	.	.
2015-06-07	7687.393563	9324.22	27126930	.	.	.	.	.	.
2015-06-14	7915.602594	9304.66	18257928	.	.	.	.	.	.
2015-06-21	6886.880676	9247.76	24704046	.	.	.	.	.	.
2015-06-28	7376.858034	9358.96	23717485	.	.	.	.	.	.
2015-07-05	7046.740272	9309.86	23967947	.	.	.	.	.	.
2015-07-12	6616.456938	8946.72	25460751	.	.	.	.	.	.
2015-07-19	6883.896656	9085	24447954	.	.	.	.	.	.
2015-07-26	6811.449276	8733.24	27039490	.	.	.	.	.	.
2015-08-02	6726.622821	8636.53	24571823	.	.	.	.	.	.
2015-08-09	6190.303924	8410.63	25408867	81.4	69.1	83.7	69.6	92.4	93.1
2015-08-16	6614.64462	8307.9	24447475	.	.	.	.	.	.
2015-08-23	6496.243056	7719.63	30520394	.	.	.	.	.	.
2015-08-30	6772.360023	8026.62	24077331	.	.	.	.	.	.
2015-09-06	6770.10926	7990.76	22013661	.	.	.	.	.	.
2015-09-13	6673.061307	8332.57	20866061	.	.	.	.	.	.
2015-09-20	6459.860415	8404.5	19706723	.	.	.	.	.	.
2015-09-27	6303.013815	8097.15	13054665	.	.	.	.	.	.
2015-10-04	5344.697037	8342.99	18792859	.	.	.	.	.	.
2015-10-11	5971.639212	8478.34	23650100	.	.	.	.	.	.
2015-10-18	6417.000734	8628.79	22119488	84.7	64.1	86.6	73.7	91.2	97.6
2015-10-25	6091.730304	8706.81	21924824	.	.	.	.	.	.
2015-11-01	5904.13722	8571.53	26349460	.	.	.	.	.	.
2015-11-08	6116.07632	8702.67	22765949	.	.	.	.	.	.
2015-11-15	5822.92998	8278.12	21620246	.	.	.	.	.	.
2015-11-22	5767.492714	8480.59	19569438	.	.	.	.	.	.
2015-11-29	5731.552584	8339.83	23294483	.	.	.	.	.	.
2015-12-06	5951.292566	8432.47	22101131	.	.	.	.	.	.
2015-12-13	5652.626049	8058.67	21747690	.	.	.	.	.	.
2015-12-20	5785.745716	8228.05	20148726	.	.	.	.	.	.
2015-12-27	5513.3874	8374.18	11155757	.	.	.	.	.	.
2016-01-03	5094.713425	8315.79	23320302	.	.	.	.	.	.
2016-01-10	5527.809588	7855.8	21796331	.	.	.	.	.	.
2016-01-17	5461.9691	7678.67	21952700	.	.	.	.	.	.
2016-01-24	5318.710272	7813.73	25737476	.	.	.	.	.	.
2016-01-31	5400.46584	8164.24	11065498	.	.	.	.	.	.
2016-02-14	4178.142814	7976.65	21610384	.	.	.	.	.	.
2016-02-21	5427.485784	8315.79	21590153	85.5	79.6	91.7	85.3	82.9	90
2016-02-28	5371.5115	8381.38	20276948	.	.	.	.	.	.
2016-03-06	5165.937	8656.74	25154913	.	.	.	.	.	.
2016-03-13	5740.33275	8746.48	26346648	.	.	.	.	.	.
2016-03-20	5487.371846	8826.16	20686409	.	.	.	.	.	.
2016-03-27	5348.992638	8713.72	20414566	.	.	.	.	.	.
2016-04-03	5426.780965	8605.16	12636153	.	.	.	.	.	.
2016-04-10	4641.285	8518.96	20740481	.	.	.	.	.	.
2016-04-17	5279.359605	8681.8	20052962	.	.	.	.	.	.
2016-04-24	5220.884313	8541.14	17270378	.	.	.	.	.	.
2016-05-01	5028.013578	8362.35	15836163	.	.	.	.	.	.
2016-05-08	4828.00368	8156.65	19280986	75.4	71.3	72.7	75.6	90	95.8
2016-05-15	4990.55814	8035.21	16278554	.	.	.	.	.	.
2016-05-22	4925.14642	8150.38	19228712	.	.	.	.	.	.
2016-05-29	4966.103024	8476.62	22543549	.	.	.	.	.	.
2016-06-05	5009.6448	8605.15	10720144	.	.	.	.	.	.
2016-06-12	4435.354066	8634.24	17486184	.	.	.	.	.	.
2016-06-19	4728.062988	8612.26	18839181	.	.	.	.	.	.
2016-06-26	4876.042706	8406.29	20706989	.	.	.	.	.	.
2016-07-03	4765.53658	8728.32	14677240	.	.	.	.	.	.
2016-07-10	4288.459904	8728.23	23517389	.	.	.	.	.	.
2016-07-17	4874.674527	8952.61	23231017	.	.	.	.	.	.
2016-07-24	4955.11527	9030.36	21522357	.	.	.	.	.	.
2016-07-31	4766.036	9008.74	19646459	.	.	.	.	.	.
2016-08-07	4671.079296	9123.07	21151658	.	.	.	.	.	.
2016-08-14	4751.418455	9152.36	20933658	.	.	.	.	.	.
2016-08-21	4553.755556	9004.68	19106001	.	.	.	.	.	.
2016-08-28	4579.152453	9117.53	20176085	.	.	.	.	.	.
2016-09-04	4650.93738	9032.38	23003485	.	.	.	.	.	.
2016-09-11	4853.76	9031.51	10761177	.	.	.	.	.	.
2016-09-18	3653.548384	9003.41	18435835	.	.	.	.	.	.
2016-09-25	4451.08752	9229.34	9774466	.	.	.	.	.	.
2016-10-02	3707.56604	9219.52	15190060	.	.	.	.	.	.
2016-10-09	4481.242982	9311.79	14099344	.	.	.	.	.	.
2016-10-16	4135.71384	9150.67	16867995	.	.	.	.	.	.
2016-10-23	4343.89755	9333.94	16375082	.	.	.	.	.	.
2016-10-30	4125.372995	9283.2	14558306	76.9	70.8	64.9	74.3	97.7	101.1
2016-11-06	4042.326155	9102.97	21524824	.	.	.	.	.	.
2016-11-13	4142.02584	8955.27	19979138	.	.	.	.	.	.
2016-11-20	4099.25934	9009.78	20371341	.	.	.	.	.	.
2016-11-27	4156.382672	9167.33	21357464	.	.	.	.	.	.
2016-12-04	4230.616248	9194.46	19210242	.	.	.	.	.	.
2016-12-11	4051.17895	9402.05	18793745	.	.	.	.	.	.
2016-12-18	4166.231112	9316.06	15937816	.	.	.	.	.	.
2016-12-25	3994.563776	9088.99	12375581	.	.	.	.	.	.
;
proc mi data = final seed=899603 out=miout_final;
var mood_economic	mood_government	 mood_investment 	mood_global	 mood_possibility;
monotone
reg(mood_economic	mood_government	 mood_investment 	mood_global	 mood_possibility);
run;
proc print data=miout_final;
run;

<log>

685  data final;
686  input date  search_volume   open_price  volume  mood_prive  mood_economic   mood_government mood_investment
686! mood_global mood_possibility
687  ;
688  informat date yymmdd.;
689  format date yymmdd10.;
690  datalines;

NOTE: The data set WORK.FINAL has 155 observations and 10 variables.
NOTE: DATA statement used (Total process time):
      real time           0.02 seconds
      cpu time            0.00 seconds


846  ;
847  proc mi data = final seed=899603 out=miout_final;
848  var mood_economic   mood_government  mood_investment    mood_global  mood_possibility;
849  monotone
850  reg(mood_economic   mood_government  mood_investment    mood_global  mood_possibility);
851  run;

WARNING: The imputed variable mood_economic in the MONOTONE statement is the leading variable in the VAR list. Missing
         values for this variable will not be imputed.
WARNING: The default number of imputations has been changed from 5 to 25.
ERROR: Each observation has analysis variables either all missing or all observed in the data set.
NOTE: The SAS System stopped processing this step because of errors.
WARNING: The data set WORK.MIOUT_FINAL may be incomplete.  When this step was stopped there were 0 observations and 11
         variables.
WARNING: Data set WORK.MIOUT_FINAL was not replaced because this step was stopped.
NOTE: PROCEDURE MI used (Total process time):
      real time           0.08 seconds
      cpu time            0.04 seconds



852  proc print data=miout_final;
853  run;

NOTE: No observations in data set WORK.MIOUT_FINAL.
NOTE: PROCEDURE PRINT used (Total process time):
      real time           0.00 seconds
      cpu time            0.00 seconds


Contributor
Posts: 57

Re: multiple imputation

Posted in reply to karen8169

Soooooo, what's your question?

Contributor
Posts: 43

Re: multiple imputation

Posted in reply to statistician13

I want to higher the frequency of data from quarter to week. As you can see above, the mood data are merely quarterly.

Contributor
Posts: 57

Re: multiple imputation

Posted in reply to karen8169

Are you able to make assumptiosn about the distribution of weekly  frequencies?  Can they be assumed to be uniformly distributed throughout any given month?

Contributor
Posts: 43

Re: multiple imputation

Posted in reply to statistician13

Can I get every distribution from the quarterly data and then mimic weekly data? Where can I find such codes?

Ask a Question
Discussion stats
  • 4 replies
  • 231 views
  • 0 likes
  • 2 in conversation