Reporting binomial logistic regression from R results
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 at gmail.com> Sent: Monday, November 12, 2018 1:48 PM To: PIKAL Petr <petr.pikal at 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, ?2(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 (?2(1) = 22.3, p < 0.001) and the system A (?2(1) = 58.7, p < 0.001), as well as that the system C led to significantly higher identification accuracies than the system A (?2(1) = 12, p < 0.001).? Best wishes FJ
On Mon, Nov 12, 2018 at 10:05 AM PIKAL Petr <petr.pikal at precheza.cz<mailto:petr.pikal at 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 at r-project.org<mailto:r-help-bounces at r-project.org>> On Behalf Of Frodo Jedi Sent: Monday, November 12, 2018 2:08 AM To: r-help at r-project.org<mailto:r-help at 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]]
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