Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Nahla Betelmal <nahlaib@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: sign test output |

Date |
Thu, 17 Jan 2013 07:52:21 +0000 |

Thank you Maarten and Nick for the great help. So, in this case I would reject the null in favour of the alternative u>0 as p value 0.000. However, using t-test on the same sample provided the opposite (i.e. accept the null). ttest DA_T_1 == 0 One-sample t test ------------------------------------------------------------------------------ Variable | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- DA_T_1 | 346 1.564346 1.68628 31.36663 -1.752338 4.88103 ------------------------------------------------------------------------------ mean = mean(DA_T_1) t = 0.9277 Ho: mean = 0 degrees of freedom = 345 Ha: mean < 0 Ha: mean != 0 Ha: mean > 0 Pr(T < t) = 0.8229 Pr(|T| > |t|) = 0.3542 Pr(T > t) = 0.1771 I think this is due to the distribution of the sample, so I performed K-S normality test. It shows that data is not normally distributed, hence I should use the non-parametric sign test instead of t-test. In other words I would reject the null u=0 in favor of u>0 , right? ksmirnov DA_T_1 = normal((DA_T_1-DA_T_1_mu)/ DA_T_1_s) One-sample Kolmogorov-Smirnov test against theoretical distribution normal((DA_T_1-DA_T_1_mu)/ DA_T_1_s) Smaller group D P-value Corrected ---------------------------------------------- DA_T_1: 0.4878 0.000 Cumulative: -0.4330 0.000 Combined K-S: 0.4878 0.000 0.000 N.B. Thank you so much Nick for the robust test you mentioned, I will use that as well) Many thanks Nahla On 16 January 2013 09:33, Nick Cox <njcoxstata@gmail.com> wrote: > In addition, it could be as or more useful to think in terms of > confidence intervals. With this sample size and average, 0.5 lies well > outside 95% intervals for the probability of being positive, and that > is robust to method of calculation: > > . cii 346 221 > > -- Binomial Exact -- > Variable | Obs Mean Std. Err. [95% Conf. Interval] > -------------+--------------------------------------------------------------- > | 346 .6387283 .0258248 .5856497 .6894096 > > . cii 346 221, jeffreys > > ----- Jeffreys ----- > Variable | Obs Mean Std. Err. [95% Conf. Interval] > -------------+--------------------------------------------------------------- > | 346 .6387283 .0258248 .5871262 .6880204 > > . cii 346 221, wilson > > ------ Wilson ------ > Variable | Obs Mean Std. Err. [95% Conf. Interval] > -------------+--------------------------------------------------------------- > | 346 .6387283 .0258248 .5868449 .6875651 > > Nick > > On Wed, Jan 16, 2013 at 9:13 AM, Maarten Buis <maartenlbuis@gmail.com> wrote: >> On Wed, Jan 16, 2013 at 9:38 AM, Nahla Betelmal wrote: >>> I have generated this output using non-parametric test "one sample >>> sign test" with null: U=0 , & Ua > 0 >>> >>> However, I do not understand the output. where is the p-value? is it >>> 0.5 in all cases or the 0.000 ( as in the first and third cases) and >>> 1.000 as in the second case? >>> >>>. signtest DA_T_1= 0 >>> >>> Sign test >>> >>> sign | observed expected >>> -------------+------------------------ >>> positive | 221 173 >>> negative | 125 173 >>> zero | 0 0 >>> -------------+------------------------ >>> all | 346 346 >>> >>> One-sided tests: >>> Ho: median of DA_T_1 = 0 vs. >>> Ha: median of DA_T_1 > 0 >>> Pr(#positive >= 221) = >>> Binomial(n = 346, x >= 221, p = 0.5) = 0.0000 >> >> The p-value is the last number, so in your case 0.0000. The stuff >> before the p-value tells you how it is computed: it is based on the >> binomial distribution, and in particular it is the chance of observing >> 221 successes or more in 346 trials when the chance of success at each >> trial is .5. For this tests this chance is the p-value, and it is very >> small, less than 0.00005. If you type in Stata -di binomialtail(346, >> 221, 0.5)- you will see that this chance is 1.381e-07, i.e. >> 0.00000001381. > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: sign test output***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: sign test output***From:*Nahla Betelmal <nahlaib@gmail.com>

**Re: st: sign test output***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: sign test output***From:*Nick Cox <njcoxstata@gmail.com>

- Prev by Date:
**Re: st: Wishlist for Stata 13** - Next by Date:
**Re: st: sieve function** - Previous by thread:
**Re: st: sign test output** - Next by thread:
**Re: st: sign test output** - Index(es):