[R] Reporting binomial logistic regression from R results

Frodo Jedi frodojedi@m@ilingli@t @ending from gm@il@com
Mon Nov 12 14:06:24 CET 2018 

Dear Petr,
thank you very much for your feedback.

Can anyone in the list advise me if the way I report the results is correct?

Kind regards

FJ


On Mon, Nov 12, 2018 at 1:02 PM PIKAL Petr <petr.pikal using precheza.cz> wrote:

> Hi Frodo
>
>
>
> I do not consider myself as an arbiter in statistical results and their
> presentation. Again your text seems to as good as any other.
>
>
>
> You should keep responses to mailing list as others could have another
> opinion.
>
>
>
> Cheers
>
> Petr
>
>
>
>
>
> *From:* Frodo Jedi <frodojedi.mailinglist using gmail.com>
> *Sent:* Monday, November 12, 2018 1:48 PM
> *To:* PIKAL Petr <petr.pikal using precheza.cz>
> *Subject:* Re: [R] Reporting binomial logistic regression from R results
>
>
>
> Dear Petr,
>
> many thanks for your reply. I was wondering whether in your opinion it is
> correct to report in a journal the following text:
>
>
>
>
>
> “A logistic regression was performed to ascertain the effects of the
> system type on the likelihood that participants report correct
> identifications. The logistic regression model was statistically
> significant, χ2(3) = 354.6, p < 0.001, indicating an overall effect of the
> system type on participants' identification performances. The Wald test was
> used to compare the model coefficients related to the three systems.
> Results showed that participants’ accuracy was significantly lower for the
> system B compared to both the system C (χ2(1) = 22.3, p < 0.001) and the
> system A (χ2(1) = 58.7, p < 0.001), as well as that the system C led to
> significantly higher identification accuracies than the system A (χ2(1) =
> 12, p < 0.001).”
>
>
>
>
>
> Best wishes
>
>
>
> FJ
>
>
>
>
>
>
>
>
>
>
>
> On Mon, Nov 12, 2018 at 10:05 AM PIKAL Petr <petr.pikal using precheza.cz>
> wrote:
>
> Dear Frodo (or Jedi)
>
> The results seems to confirm your assumption that 3 systems are different.
> How you should present results probably depends on how it is usual to
> report such results in your environment.
>
> BTW. It seems to me like homework and this list has no homework policy
> (Sorry, if I am mistaken).
>
> Cheers
> Petr
> > -----Original Message-----
> > From: R-help <r-help-bounces using r-project.org> On Behalf Of Frodo Jedi
> > Sent: Monday, November 12, 2018 2:08 AM
> > To: r-help using r-project.org
> > Subject: [R] Reporting binomial logistic regression from R results
> >
> > Dear list members,
> > I need some help in understanding whether I am doing correctly a binomial
> > logistic regression and whether I am interpreting the results in the
> correct way.
> > Also I would need an advice regarding the reporting of the results from
> the R
> > functions.
> >
> > I want to report the results of a binomial logistic regression where I
> want to
> > assess difference between the 3 levels of a factor (called System) on the
> > dependent variable (called Response) taking two values, 0 and 1. My goal
> is to
> > understand if the effect of the 3 systems (A,B,C) in System affect
> differently
> > Response in a significant way. I am basing my analysis on this URL:
> > https://stats.idre.ucla.edu/r/dae/logit-regression/
> >
> > This is the result of my analysis:
> >
> > > fit <- glm(Response ~ System, data = scrd, family = "binomial")
> > > summary(fit)
> >
> > Call:
> > glm(formula = Response ~ System, family = "binomial", data = scrd)
> >
> > Deviance Residuals:
> >     Min       1Q   Median       3Q      Max
> > -2.8840   0.1775   0.2712   0.2712   0.5008
> >
> > Coefficients:
> >              Estimate Std. Error z value Pr(>|z|)
> > (Intercept)    3.2844     0.2825  11.626  < 2e-16 ***
> > SystemB  -1.2715     0.3379  -3.763 0.000168 ***
> > SystemC    0.8588     0.4990   1.721 0.085266 .
> > ---
> > Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> >
> > (Dispersion parameter for binomial family taken to be 1)
> >
> >     Null deviance: 411.26  on 1023  degrees of freedom Residual deviance:
> > 376.76  on 1021  degrees of freedom
> > AIC: 382.76
> >
> > Number of Fisher Scoring iterations: 6
> > Following this analysis I perform the wald test in order to understand
> whether
> > there is an overall effect of System:
> >
> > library(aod)
> >
> > > wald.test(b = coef(fit), Sigma = vcov(fit), Terms = 1:3)
> > Wald test:
> > ----------
> >
> > Chi-squared test:
> > X2 = 354.6, df = 3, P(> X2) = 0.0
> > The chi-squared test statistic of 354.6, with 3 degrees of freedom is
> associated
> > with a p-value < 0.001 indicating that the overall effect of System is
> statistically
> > significant.
> >
> > Now I check whether there are differences between the coefficients using
> again
> > the wald test:
> >
> > # Here difference between system B and C:
> >
> > > l <- cbind(0, 1, -1)
> > > wald.test(b = coef(fit), Sigma = vcov(fit), L = l)
> > Wald test:
> > ----------
> >
> > Chi-squared test:
> > X2 = 22.3, df = 1, P(> X2) = 2.3e-06
> >
> >
> >
> > # Here difference between system A and C:
> >
> > > l <- cbind(1, 0, -1)
> > > wald.test(b = coef(fit), Sigma = vcov(fit), L = l)
> > Wald test:
> > ----------
> >
> > Chi-squared test:
> > X2 = 12.0, df = 1, P(> X2) = 0.00052
> >
> >
> >
> > # Here difference between system A and B:
> >
> > > l <- cbind(1, -1, 0)
> > > wald.test(b = coef(fit), Sigma = vcov(fit), L = l)
> > Wald test:
> > ----------
> >
> > Chi-squared test:
> > X2 = 58.7, df = 1, P(> X2) = 1.8e-14
> >
> > My understanding is that from this analysis I can state that the three
> systems
> > lead to a significantly different Response. Am I right? If so, how
> should I report
> > the results of this analysis? What is the correct way?
> >
> >
> > Thanks in advance
> >
> > Best wishes
> >
> > FJ
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> Osobní údaje: Informace o zpracování a ochraně osobních údajů obchodních
> partnerů PRECHEZA a.s. jsou zveřejněny na:
> https://www.precheza.cz/zasady-ochrany-osobnich-udaju/ | Information
> about processing and protection of business partner’s personal data are
> available on website:
> https://www.precheza.cz/en/personal-data-protection-principles/
> Důvěrnost: Tento e-mail a jakékoliv k němu připojené dokumenty jsou
> důvěrné a podléhají tomuto právně závaznému prohláąení o vyloučení
> odpovědnosti: https://www.precheza.cz/01-dovetek/ | This email and any
> documents attached to it may be confidential and are subject to the legally
> binding disclaimer: https://www.precheza.cz/en/01-disclaimer/
>
>

	[[alternative HTML version deleted]]

More information about the R-help mailing list