In support of CTABLES

[Buhi, Eric]

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[Jon K Peck]

In the gui, turn on totals via Categories and Totals.  Then, in the Summary Statistics subdialog, check Custom Summary Statistics for Totals and Subtotals, and off you go.

Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
[hidden email]
new phone: [phone]




From:        "John F Hall" <[hidden email]>
To:        Jon K Peck/Chicago/IBM@IBMUS
Cc:        <[hidden email]>, "'David Marso'" <[hidden email]>, <[hidden email]>, "'Poes, Matthew Joseph'" <[hidden email]>, "'ViAnn Beadle'" <[hidden email]>
Date:        03/18/2012 11:25 PM
Subject:        RE: In support of CTABLES

---

Jon
 
Waking up at 4:15 am, it was a delight to find your mail.  This is brilliant.  I’ve modified your syntax to suit my data set, but I need to work out how to get the syntax from the GUI since that’s what students will use.  Here are the tables (and syntax) I produced:
 
 
1: Zero order
 
ctables
   /tables by happy [c] [ROWPCT.COUNT TOTALS[COUNT]]
   /CATEGORIES VARIABLES=happy TOTAL=YES POSITION=AFTER .
 
 

Q.53 How [happy] are you these days?
Not too happy	Fairly Happy	Very happy	Total
Row N %	Row N %	Row N %	Count
6.2%	55.7%	38.1%	926

 
 
2: First order
 
CTABLES
  /TABLE marital [C] BY happy [C][ROWPCT.COUNT TOTALS[COUNT]]
  /CATEGORIES VARIABLES= marital happy TOTAL=YES POSITION=AFTER .
 
 

		Q.53 How [happy] are you these days?
		Not too happy	Fairly Happy	Very happy	Total
		Row N %	Row N %	Row N %	Count
Marital status of respondent	Single	4.7%	70.0%	25.3%	150
	Married	4.5%	51.9%	43.6%	649
	Widowed	17.3%	59.2%	23.5%	98
	Divorced or separated	13.8%	55.2%	31.0%	29
	Total	6.2%	55.7%	38.1%	926

 
 

		Q.53 How [happy] are you these days?
		Not too happy	Fairly Happy	Very happy	Total
		Row N %	Row N %	Row N %	Count
Sex of Respondent	Men	6.2%	59.7%	34.0%	385
	Women	6.1%	52.9%	41.0%	541
	Total	6.2%	55.7%	38.1%	926

 
The format of these tables is exactly what I want for earlier tutorials (and for reports): it’s a shame I can’t get them using CROSSTABS.  
 
3: Second order
 
CTABLES
  /TABLE marital [C] BY happy [C][ROWPCT.COUNT TOTALS[COUNT]]
  /CATEGORIES VARIABLES= marital happy TOTAL=YES POSITION=AFTER .
 

Q.53 How [happy] are you these days? Total
		Sex of Respondent
		Total	Men	Women
		Count	Count	Count
Marital status of respondent	Total	926	385	541
	Single	150	76	74
	Married	649	288	361
	Widowed	98	15	83
	Divorced or separated	29	6	23

 
 
OOPS!!  
 
45 year old Algol programming instinct made me try:
 
CTABLES
  /TABLE marital [C] > sex [c] by happy [C][ROWPCT.COUNT TOTALS[COUNT]]
  /CATEGORIES VARIABLES= marital sex happy TOTAL=YES POSITION=after .
 
 

				Q.53 How [happy] are you these days?
				Not too happy	Fairly Happy	Very happy	Total
				Row N %	Row N %	Row N %	Count
Marital status of respondent	Single	Sex of Respondent	Men	5.3%	75.0%	19.7%	76
			Women	4.1%	64.9%	31.1%	74
			Total	4.7%	70.0%	25.3%	150
	Married	Sex of Respondent	Men	5.2%	55.6%	39.2%	288
			Women	3.9%	49.0%	47.1%	361
			Total	4.5%	51.9%	43.6%	649
	Widowed	Sex of Respondent	Men	26.7%	60.0%	13.3%	15
			Women	15.7%	59.0%	25.3%	83
			Total	17.3%	59.2%	23.5%	98
	Divorced or separated	Sex of Respondent	Men	16.7%	66.7%	16.7%	6
			Women	13.0%	52.2%	34.8%	23
			Total	13.8%	55.2%	31.0%	29
	Total	Sex of Respondent	Men	6.2%	59.7%	34.0%	385
			Women	6.1%	52.9%	41.0%	541
			Total	6.2%	55.7%	38.1%	926

 
 
CTABLES
  /TABLE  sex [c] >  marital [C] by happy [C] [ROWPCT.COUNT TOTALS[COUNT]]
  /CATEGORIES VARIABLES= marital sex happy TOTAL=YES POSITION=after .
 
 

				Q.53 How [happy] are you these days?
				Not too happy	Fairly Happy	Very happy	Total
				Row N %	Row N %	Row N %	Count
Sex of Respondent	Men	Marital status of respondent	Single	5.3%	75.0%	19.7%	76
			Married	5.2%	55.6%	39.2%	288
			Widowed	26.7%	60.0%	13.3%	15
			Divorced or separated	16.7%	66.7%	16.7%	6
			Total	6.2%	59.7%	34.0%	385
	Women	Marital status of respondent	Single	4.1%	64.9%	31.1%	74
			Married	3.9%	49.0%	47.1%	361
			Widowed	15.7%	59.0%	25.3%	83
			Divorced or separated	13.0%	52.2%	34.8%	23
			Total	6.1%	52.9%	41.0%	541
	Total	Marital status of respondent	Single	4.7%	70.0%	25.3%	150
			Married	4.5%	51.9%	43.6%	649
			Widowed	17.3%	59.2%	23.5%	98
			Divorced or separated	13.8%	55.2%	31.0%	29
			Total	6.2%	55.7%	38.1%	926

 
There’s rather too much data in these tables: they might be more informative if the Total rows were dropped, leaving just the Total column as below, but tidier:
 

		Q.53 How [happy] are you these days?
		Not too happy	Fairly Happy			Very happy	Total
		Row N %	Row N %			Row N %	Count
Total		6.2%		55.7%	38.1%			926

 

Sex of respondent					Men			6.2%		59.7%	34.0%			385
					Women			6.1%		52.9%	41.0%			541
	Marital status of respondent			Single		Men	5.3%		75.0%			19.7%	76
						Women	4.1%		64.9%			31.1%	74
				Married		Men	5.2%		55.6%			39.2%	288
						Women	3.9%		49.0%			47.1%	361
				Widowed		Men	26.7%		60.0%			13.3%	15
						Women	15.7%		59.0%			25.3%	83
				Divorced or separated		Men	16.7%		66.7%			16.7%	6
						Women	13.0%		52.2%			34.8%	23

 
. . . or perhaps analyse only one category at a time to generate smaller tables.
 
The next step would be to take a criterion value for the dependent variable, ie value 1 (Not too happy) or value 3 (Very happy) and produce a summary table as in my earlier mail.  In that, I used “Very happy”, but being happy is normative, so I suspect it would be more interesting to pursue the “Not too happy” category.
 
I still need to check out David’s syntax, but now that I’ve been let loose with a new toy, preparation of and planting in the vegetable garden will be a less attractive proposition: the next few days are going to be fun.
Cordialement
John
 
Email:     johnfhall@...
Website: www.surveyresearch.weebly.com
Skype:   surveyresearcher1
Phone:    (+33) (0) 2.33.45.91.47
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
From: Jon K Peck [mailto:peck@...]
Sent: 18 March 2012 23:35
To: John F Hall
Subject: RE: In support of CTABLES
 
One comment jumps out at me

"This table is easier to interpret, but we have lost the base for percentaging at the end of each row.  Without special programming beyond the scope of this tutorial, SPSS cannot produce a table with n instead of 100%.   A more useful table would look like this:"

In the Summary Statistics subdialog (and, of course, in the TABLE subcommand), you can choose different statistics for totals from the items tabulated.

For example,
CTABLES
 /TABLE gender [C] BY jobcat [C][ROWPCT.COUNT TOTALS[COUNT]]
 /CATEGORIES VARIABLES=gender jobcat TOTAL=YES POSITION=AFTER .

gives you percents on the non-total cells and counts for the totals cells.

Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
peck@...
new phone: [phone]