One sample binomial test about a population proportion

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One sample binomial test about a population proportion

ANDRES ALBERTO BURGA LEON
Hello to everybody:

I'm using SPSS 21 to test a hypothesis about a population proportion. For that I use the binomial test, with the following syntax:

DATA LIST FREE
/ ite_24 peso.
BEGIN DATA
1 31
0 94
END DATA.

WEIGHT BY peso.

NPTESTS
  /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35 SUCCESSCATEGORICAL=LIST(1)
    SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
  /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
  /CRITERIA ALPHA=0.01 CILEVEL=99.

I understand that SPSS does a Z test approximation when n >= 25. What I don’t understand (and haven’t found any reference), is why this Z test uses some kind of Yates continuity correction, because it adds and subtracts 0.5 to the quantity of observed 1 categories and calculates two Z, reporting the smallest.

For hand calculations I use te following algorithm, which gave me a significant one tailed result at .01

Z = (p – P) / SQRT(P * (1 – P) / n)

P: population proportion

p : sample proportion

n : sample size

SPSS gave me at .01 a non-significant result.

Any suggestions?

Kindly

Andres

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Re: One sample binomial test about a population proportion

Bruce Weaver
Administrator
Perhaps you'll find the good old (and now deprecated) NPAR TESTS command more to your liking.  It gives an exact one-tailed p-value of .009 for your data.  (And it does not conjure up any of that model viewer output!)

NPAR TESTS
  /BINOMIAL (0.35)=ite_24
  /MISSING ANALYSIS.

In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.

HTH.


ANDRES ALBERTO BURGA LEON wrote
Hello to everybody:

I'm using SPSS 21 to test a hypothesis about a population proportion. For that I use the binomial test, with the following syntax:

DATA LIST FREE
/ ite_24 peso.
BEGIN DATA
1 31
0 94
END DATA.

WEIGHT BY peso.

NPTESTS
  /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35 SUCCESSCATEGORICAL=LIST(1)
    SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
  /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
  /CRITERIA ALPHA=0.01 CILEVEL=99.

I understand that SPSS does a Z test approximation when n >= 25. What I don’t understand (and haven’t found any reference), is why this Z test uses some kind of Yates continuity correction, because it adds and subtracts 0.5 to the quantity of observed 1 categories and calculates two Z, reporting the smallest.

For hand calculations I use te following algorithm, which gave me a significant one tailed result at .01

Z = (p – P) / SQRT(P * (1 – P) / n)

P: population proportion

p : sample proportion

n : sample size

SPSS gave me at .01 a non-significant result.

Any suggestions?

Kindly

Andres

=====================
To manage your subscription to SPSSX-L, send a message to
[hidden email] (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
SIGNOFF SPSSX-L
For a list of commands to manage subscriptions, send the command
INFO REFCARD
--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

PLEASE NOTE THE FOLLOWING: 
1. My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above.
2. The SPSSX Discussion forum on Nabble is no longer linked to the SPSSX-L listserv administered by UGA (https://listserv.uga.edu/).
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Re: One sample binomial test about a population proportion

Jon K Peck
The NPAR dialogs are now show under the Legacy submenu, but I am not aware of any place where they are declared to be deprecated.


Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
[hidden email]
phone: 720-342-5621




From:        Bruce Weaver <[hidden email]>
To:        [hidden email],
Date:        06/11/2013 11:53 AM
Subject:        Re: [SPSSX-L] One sample binomial test about a population              proportion
Sent by:        "SPSSX(r) Discussion" <[hidden email]>




Perhaps you'll find the good old (and now deprecated) NPAR TESTS command more
to your liking.  It gives an exact one-tailed p-value of .009 for your data.
(And it does not conjure up any of that model viewer output!)

NPAR TESTS
 /BINOMIAL (0.35)=ite_24
 /MISSING ANALYSIS.

In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.

HTH.



ANDRES ALBERTO BURGA LEON wrote
> Hello to everybody:
>
> I'm using SPSS 21 to test a hypothesis about a population proportion. For
> that I use the binomial test, with the following syntax:
>
> DATA LIST FREE
> / ite_24 peso.
> BEGIN DATA
> 1 31
> 0 94
> END DATA.
>
> WEIGHT BY peso.
>
> NPTESTS
>   /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35
> SUCCESSCATEGORICAL=LIST(1)
>     SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
>   /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
>   /CRITERIA ALPHA=0.01 CILEVEL=99.
>
> I understand that SPSS does a Z test approximation when n >= 25. What I
> don&#8217;t understand (and haven&#8217;t found any reference), is why
> this Z test uses some kind of Yates continuity correction, because it adds
> and subtracts 0.5 to the quantity of observed 1 categories and calculates
> two Z, reporting the smallest.
>
> For hand calculations I use te following algorithm, which gave me a
> significant one tailed result at .01
>
> Z = (p &#8211; P) / SQRT(P * (1 &#8211; P) / n)
>
> P: population proportion
>
> p : sample proportion
>
> n : sample size
>
> SPSS gave me at .01 a non-significant result.
>
> Any suggestions?
>
> Kindly
>
> Andres
>
> =====================
> To manage your subscription to SPSSX-L, send a message to

> LISTSERV@.UGA

>  (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
> SIGNOFF SPSSX-L
> For a list of commands to manage subscriptions, send the command
> INFO REFCARD





-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
View this message in context:
http://spssx-discussion.1045642.n5.nabble.com/One-sample-binomial-test-about-a-population-proportion-tp5720671p5720672.html
Sent from the SPSSX Discussion mailing list archive at Nabble.com.

=====================
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[hidden email] (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
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For a list of commands to manage subscriptions, send the command
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Re: One sample binomial test about a population proportion

Bruce Weaver
Administrator
My apologies.  Too strong a word.  However, it does seem to me that use of NPAR TESTS is discouraged.  (You might prefer to say it the other way around -- i.e., use of NPTESTS is encouraged.)


Jon K Peck wrote
The NPAR dialogs are now show under the Legacy submenu, but I am not aware
of any place where they are declared to be deprecated.


Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
[hidden email]
phone: 720-342-5621




From:   Bruce Weaver <[hidden email]>
To:     [hidden email],
Date:   06/11/2013 11:53 AM
Subject:        Re: [SPSSX-L] One sample binomial test about a population
           proportion
Sent by:        "SPSSX(r) Discussion" <[hidden email]>



Perhaps you'll find the good old (and now deprecated) NPAR TESTS command
more
to your liking.  It gives an exact one-tailed p-value of .009 for your
data.
(And it does not conjure up any of that model viewer output!)

NPAR TESTS
  /BINOMIAL (0.35)=ite_24
  /MISSING ANALYSIS.

In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.

HTH.



ANDRES ALBERTO BURGA LEON wrote
> Hello to everybody:
>
> I'm using SPSS 21 to test a hypothesis about a population proportion.
For
> that I use the binomial test, with the following syntax:
>
> DATA LIST FREE
> / ite_24 peso.
> BEGIN DATA
> 1 31
> 0 94
> END DATA.
>
> WEIGHT BY peso.
>
> NPTESTS
>   /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35
> SUCCESSCATEGORICAL=LIST(1)
>     SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
>   /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
>   /CRITERIA ALPHA=0.01 CILEVEL=99.
>
> I understand that SPSS does a Z test approximation when n >= 25. What I
> don’t understand (and haven’t found any reference), is why
> this Z test uses some kind of Yates continuity correction, because it
adds
> and subtracts 0.5 to the quantity of observed 1 categories and
calculates
> two Z, reporting the smallest.
>
> For hand calculations I use te following algorithm, which gave me a
> significant one tailed result at .01
>
> Z = (p – P) / SQRT(P * (1 – P) / n)
>
> P: population proportion
>
> p : sample proportion
>
> n : sample size
>
> SPSS gave me at .01 a non-significant result.
>
> Any suggestions?
>
> Kindly
>
> Andres
>
> =====================
> To manage your subscription to SPSSX-L, send a message to

> LISTSERV@.UGA

>  (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
> SIGNOFF SPSSX-L
> For a list of commands to manage subscriptions, send the command
> INFO REFCARD





-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
View this message in context:
http://spssx-discussion.1045642.n5.nabble.com/One-sample-binomial-test-about-a-population-proportion-tp5720671p5720672.html

Sent from the SPSSX Discussion mailing list archive at Nabble.com.

=====================
To manage your subscription to SPSSX-L, send a message to
[hidden email] (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
SIGNOFF SPSSX-L
For a list of commands to manage subscriptions, send the command
INFO REFCARD
--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

PLEASE NOTE THE FOLLOWING: 
1. My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above.
2. The SPSSX Discussion forum on Nabble is no longer linked to the SPSSX-L listserv administered by UGA (https://listserv.uga.edu/).
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Re: One sample binomial test about a population proportion

ANDRES ALBERTO BURGA LEON
In reply to this post by Bruce Weaver
Thank you, I 've allready done this, but I'm still trying to figure out why the NPTESTS uses the mentioned algorithm

Andres



-----"SPSSX(r) Discussion" <[hidden email]> escribió: -----
Para: [hidden email]
De: Bruce Weaver
Enviado por: "SPSSX(r) Discussion"
Fecha: 11/06/2013 13:23
Asunto: Re: One sample binomial test about a population proportion

Perhaps you'll find the good old (and now deprecated) NPAR TESTS command more
to your liking.  It gives an exact one-tailed p-value of .009 for your data.
(And it does not conjure up any of that model viewer output!)

NPAR TESTS
  /BINOMIAL (0.35)=ite_24
  /MISSING ANALYSIS.

In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.

HTH.



ANDRES ALBERTO BURGA LEON wrote

> Hello to everybody:
>
> I'm using SPSS 21 to test a hypothesis about a population proportion. For
> that I use the binomial test, with the following syntax:
>
> DATA LIST FREE
> / ite_24 peso.
> BEGIN DATA
> 1 31
> 0 94
> END DATA.
>
> WEIGHT BY peso.
>
> NPTESTS
>   /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35
> SUCCESSCATEGORICAL=LIST(1)
>     SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
>   /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
>   /CRITERIA ALPHA=0.01 CILEVEL=99.
>
> I understand that SPSS does a Z test approximation when n >= 25. What I
> don’t understand (and haven’t found any reference), is why
> this Z test uses some kind of Yates continuity correction, because it adds
> and subtracts 0.5 to the quantity of observed 1 categories and calculates
> two Z, reporting the smallest.
>
> For hand calculations I use te following algorithm, which gave me a
> significant one tailed result at .01
>
> Z = (p – P) / SQRT(P * (1 – P) / n)
>
> P: population proportion
>
> p : sample proportion
>
> n : sample size
>
> SPSS gave me at .01 a non-significant result.
>
> Any suggestions?
>
> Kindly
>
> Andres
>
> =====================
> To manage your subscription to SPSSX-L, send a message to

> LISTSERV@.UGA

>  (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
> SIGNOFF SPSSX-L
> For a list of commands to manage subscriptions, send the command
> INFO REFCARD





-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
View this message in context: http://spssx-discussion.1045642.n5.nabble.com/One-sample-binomial-test-about-a-population-proportion-tp5720671p5720672.html
Sent from the SPSSX Discussion mailing list archive at Nabble.com.

=====================
To manage your subscription to SPSSX-L, send a message to
[hidden email] (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
SIGNOFF SPSSX-L
For a list of commands to manage subscriptions, send the command
INFO REFCARD

====================To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD
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Re: One sample binomial test about a population proportion

MOram

 

Hi Andres,

 

Am I right in thinking you want to know what & why Yate’s correction is used?

 

If so (and only as far as I understand it), its because the distribution of the squared normal deviate (chi-squared) assumes the measures are from a continuous variable. That is, the scores could take on any value. If they can’t – as with counts – then the calculated value of chi-square is too high. Yate’s correction improves the accuracy of the estimate. Your algorithm uses the probabilities, so assumes a continuous variable (the p value). This will give inflated type 1 errors (rejecting the null hypothesis when you shouldn’t).

 

I’m afraid I don’t know of a good reference for the details of the argument (i.e. the proof that using (deviation-0.5) is the best one to use), but a little thought on the impact of squaring the normalised deviations [Poisson approximation is (observed-expected)^2/expected] when your values are rounded to integer values gives you the general idea.

 

Mike

 

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of ANDRES ALBERTO BURGA LEON
Sent: 12 June 2013 00:37
To: [hidden email]
Subject: Re: One sample binomial test about a population proportion

 

Thank you, I 've allready done this, but I'm still trying to figure out why the NPTESTS uses the mentioned algorithm

Andres



-----"SPSSX(r) Discussion" <[hidden email]> escribió: -----

Para: [hidden email]
De: Bruce Weaver
Enviado por: "SPSSX(r) Discussion"
Fecha: 11/06/2013 13:23
Asunto: Re: One sample binomial test about a population proportion

Perhaps you'll find the good old (and now deprecated) NPAR TESTS command more
to your liking.  It gives an exact one-tailed p-value of .009 for your data.
(And it does not conjure up any of that model viewer output!)

NPAR TESTS
  /BINOMIAL (0.35)=ite_24
  /MISSING ANALYSIS.

In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.

HTH.



ANDRES ALBERTO BURGA LEON wrote
> Hello to everybody:
>
> I'm using SPSS 21 to test a hypothesis about a population proportion. For
> that I use the binomial test, with the following syntax:
>
> DATA LIST FREE
> / ite_24 peso.
> BEGIN DATA
> 1 31
> 0 94
> END DATA.
>
> WEIGHT BY peso.
>
> NPTESTS
>   /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35
> SUCCESSCATEGORICAL=LIST(1)
>     SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
>   /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
>   /CRITERIA ALPHA=0.01 CILEVEL=99.
>
> I understand that SPSS does a Z test approximation when n >= 25. What I
> don’t understand (and haven’t found any reference), is why
> this Z test uses some kind of Yates continuity correction, because it adds
> and subtracts 0.5 to the quantity of observed 1 categories and calculates
> two Z, reporting the smallest.
>
> For hand calculations I use te following algorithm, which gave me a
> significant one tailed result at .01
>
> Z = (p – P) / SQRT(P * (1 – P) / n)
>
> P: population proportion
>
> p : sample proportion
>
> n : sample size
>
> SPSS gave me at .01 a non-significant result.
>
> Any suggestions?
>
> Kindly
>
> Andres
>
> =====================
> To manage your subscription to SPSSX-L, send a message to

> [hidden email]

>  (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
> SIGNOFF SPSSX-L
> For a list of commands to manage subscriptions, send the command
> INFO REFCARD





-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
View this message in context: http://spssx-discussion.1045642.n5.nabble.com/One-sample-binomial-test-about-a-population-proportion-tp5720671p5720672.html
Sent from the SPSSX Discussion mailing list archive at Nabble.com.

=====================
To manage your subscription to SPSSX-L, send a message to
[hidden email] (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
SIGNOFF SPSSX-L
For a list of commands to manage subscriptions, send the command
INFO REFCARD

======= To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD

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Re: One sample binomial test about a population proportion

Rich Ulrich
"Yates's correction" is the name of the continuity correction for the 2x2 table.

This one-sample correction-for-continuity does not have any special name
that I know of.  I presume that it is validated by improvements in accuracy,
given by Monte Carlo studies.  I don't remember hearing that it has ever
been controversial, but I wonder whether the NPAR-tests does use an "exact"
estimate, based on permutations.

Yates's correction, on the other hand, has had some controversy among
high-powered statisticians.  There are articles in the 1980s, in the
"Journal of the Royal Statistical Society", discussing Fishers Exact Test
vs 2x2 Pearson test.  See

Yates, et al. JRSS Series A (1984) 147:426-463.
Shuster. JRSS Series A (1985) 148:317-327.
Upton. JRSS Series A (1992) 155:395-402.

Everyone agreed that the FET "assumes fixed marginals" and is appropriate
for that case.  Everyone agreed that Yates's correction gives 2x2 p-values that
agree more closely to the FET than the uncorrected test.  The controversy
was whether p-values from the FET were preferable when marginal totals are
not fixed.  The articles are worth reading for their close arguments on the
meaning of "p" and philosophy of what is "preferable."

In the 1984 article, Upton leant strongly against using Fishers' test. In the
1992 article, he announces own conversion, crediting the arguments of Barnard.

--
Rich Ulrich


Date: Wed, 12 Jun 2013 08:49:39 +0000
From: [hidden email]
Subject: Re: One sample binomial test about a population proportion
To: [hidden email]

 

Hi Andres,

 

Am I right in thinking you want to know what & why Yate’s correction is used?

 

If so (and only as far as I understand it), its because the distribution of the squared normal deviate (chi-squared) assumes the measures are from a continuous variable. That is, the scores could take on any value. If they can’t – as with counts – then the calculated value of chi-square is too high. Yate’s correction improves the accuracy of the estimate. Your algorithm uses the probabilities, so assumes a continuous variable (the p value). This will give inflated type 1 errors (rejecting the null hypothesis when you shouldn’t).

 

I’m afraid I don’t know of a good reference for the details of the argument (i.e. the proof that using (deviation-0.5) is the best one to use), but a little thought on the impact of squaring the normalised deviations [Poisson approximation is (observed-expected)^2/expected] when your values are rounded to integer values gives you the general idea.

 

Mike

 

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of ANDRES ALBERTO BURGA LEON
Sent: 12 June 2013 00:37
To: [hidden email]
Subject: Re: One sample binomial test about a population proportion

 

Thank you, I 've allready done this, but I'm still trying to figure out why the NPTESTS uses the mentioned algorithm

Andres



-----"SPSSX(r) Discussion" <[hidden email]> escribió: -----

Para: [hidden email]
De: Bruce Weaver
Enviado por: "SPSSX(r) Discussion"
Fecha: 11/06/2013 13:23
Asunto: Re: One sample binomial test about a population proportion

Perhaps you'll find the good old (and now deprecated) NPAR TESTS command more
to your liking.  It gives an exact one-tailed p-value of .009 for your data.
(And it does not conjure up any of that model viewer output!)

NPAR TESTS
  /BINOMIAL (0.35)=ite_24
  /MISSING ANALYSIS.

In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.

HTH.



ANDRES ALBERTO BURGA LEON wrote
> Hello to everybody:
>
> I'm using SPSS 21 to test a hypothesis about a population proportion. For
> that I use the binomial test, with the following syntax:
>
> DATA LIST FREE
> / ite_24 peso.
> BEGIN DATA
> 1 31
> 0 94
> END DATA.
>
> WEIGHT BY peso.
>
> NPTESTS
>   /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35
> SUCCESSCATEGORICAL=LIST(1)
>     SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))
>   /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE
>   /CRITERIA ALPHA=0.01 CILEVEL=99.
>
> I understand that SPSS does a Z test approximation when n >= 25. What I
> don’t understand (and haven’t found any reference), is why
> this Z test uses some kind of Yates continuity correction, because it adds
> and subtracts 0.5 to the quantity of observed 1 categories and calculates
> two Z, reporting the smallest.
>
> For hand calculations I use te following algorithm, which gave me a
> significant one tailed result at .01
>
> Z = (p – P) / SQRT(P * (1 – P) / n)
>
> P: population proportion
>
> p : sample proportion
>
> n : sample size
>
> SPSS gave me at .01 a non-significant result.
>
> Any suggestions?
>
> Kindly
>
> Andres
>


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Re: One sample binomial test about a population proportion

Bruce Weaver
Administrator
Regarding Rich's discussion of 2x2 tables below, see also Ian Campbell's Statistics in Medicine article on the N-1 chi-square.  

   http://www.iancampbell.co.uk/twobytwo/twobytwo.htm

Campbell's simulations show that when the marginal totals are not fixed, the N-1 chi-square works well for expected counts as low as 1, IIRC.


Rich Ulrich-2 wrote
"Yates's correction" is the name of the continuity correction for the 2x2 table.

This one-sample correction-for-continuity does not have any special name
that I know of.  I presume that it is validated by improvements in accuracy,
given by Monte Carlo studies.  I don't remember hearing that it has ever
been controversial, but I wonder whether the NPAR-tests does use an "exact"
estimate, based on permutations.

Yates's correction, on the other hand, has had some controversy among
high-powered statisticians.  There are articles in the 1980s, in the
"Journal of the Royal Statistical Society", discussing Fishers Exact Test
vs 2x2 Pearson test.  See

Yates, et al.  JRSS Series A (1984) 147:426-463.

Shuster.  JRSS Series A (1985) 148:317-327.

Upton.  JRSS Series A (1992) 155:395-402.  

Everyone agreed that the FET "assumes fixed marginals" and is appropriate
for that case.  Everyone agreed that Yates's correction gives 2x2 p-values that
agree more closely to the FET than the uncorrected test.  The controversy
was whether p-values from the FET were preferable when marginal totals are
not fixed.  The articles are worth reading for their close arguments on the
meaning of "p" and philosophy of what is "preferable."

In the 1984 article,
  Upton leant strongly against using Fishers' test.  In the
1992 article, he announces own conversion, crediting the
  arguments of Barnard.


--
Rich Ulrich

Date: Wed, 12 Jun 2013 08:49:39 +0000
From: [hidden email]
Subject: Re: One sample binomial test about a population proportion
To: [hidden email]









 
Hi Andres,
 
Am I right in thinking you want to know what & why Yate’s correction is used?
 
If so (and only as far as I understand it), its because the distribution of the squared normal deviate (chi-squared) assumes the measures are from a continuous
 variable. That is, the scores could take on any value. If they can’t – as with counts – then the calculated value of chi-square is too high. Yate’s correction improves the accuracy of the estimate. Your algorithm uses the probabilities, so assumes a continuous
 variable (the p value). This will give inflated type 1 errors (rejecting the null hypothesis when you shouldn’t).

 
I’m afraid I don’t know of a good reference for the details of the argument (i.e. the proof that using (deviation-0.5) is the best one to use), but a little
 thought on the impact of squaring the normalised deviations [Poisson approximation is (observed-expected)^2/expected] when your values are rounded to integer values gives you the general idea.
 
Mike
 
From: SPSSX(r) Discussion [mailto:[hidden email]]
On Behalf Of ANDRES ALBERTO BURGA LEON

Sent: 12 June 2013 00:37

To: [hidden email]

Subject: Re: One sample binomial test about a population proportion
 


Thank you, I 've allready done this, but I'm still trying to figure out why the
NPTESTS uses the mentioned algorithm


Andres






-----"SPSSX(r) Discussion" <[hidden email]> escribió: -----



Para:
[hidden email]

De: Bruce Weaver

Enviado por: "SPSSX(r) Discussion"

Fecha: 11/06/2013 13:23

Asunto: Re: One sample binomial test about a population proportion



Perhaps you'll find the good old (and now deprecated) NPAR TESTS command more

to your liking.  It gives an exact one-tailed p-value of .009 for your data.

(And it does not conjure up any of that model viewer output!)



NPAR TESTS

  /BINOMIAL (0.35)=ite_24

  /MISSING ANALYSIS.



In the GUI, Analyze > Nonparametric > Legacy Dialogs > Binomial.



HTH.







ANDRES ALBERTO BURGA LEON wrote

> Hello to everybody:

>

> I'm using SPSS 21 to test a hypothesis about a population proportion. For

> that I use the binomial test, with the following syntax:

>

> DATA LIST FREE

> / ite_24 peso.

> BEGIN DATA

> 1 31

> 0 94

> END DATA.

>

> WEIGHT BY peso.

>

> NPTESTS

>   /ONESAMPLE TEST (ite_24) BINOMIAL(TESTVALUE=0.35

> SUCCESSCATEGORICAL=LIST(1)

>     SUCCESSCONTINUOUS=CUTPOINT(MIDPOINT))

>   /MISSING SCOPE=ANALYSIS USERMISSING=EXCLUDE

>   /CRITERIA ALPHA=0.01 CILEVEL=99.

>

> I understand that SPSS does a Z test approximation when n >= 25. What I

> don’t understand (and haven’t found any reference), is why

> this Z test uses some kind of Yates continuity correction, because it adds

> and subtracts 0.5 to the quantity of observed 1 categories and calculates

> two Z, reporting the smallest.

>

> For hand calculations I use te following algorithm, which gave me a

> significant one tailed result at .01

>

> Z = (p – P) / SQRT(P * (1 – P) / n)

>

> P: population proportion

>

> p : sample proportion

>

> n : sample size

>

> SPSS gave me at .01 a non-significant result.

>

> Any suggestions?

>

> Kindly

>

> Andres

>
--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

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