DocBuckets

130 reputation

bio	website	mic.wustl.edu
	location	St. Louis, MO
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visits	member for	1 year, 3 months
	seen	34 mins ago
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Intermediate statistics, mostly self taught so don't take me too seriously.

	130 reputation	bio	website	mic.wustl.edu	visits	member for	1 year, 3 months
7 badges		location	St. Louis, MO		seen	34 mins ago

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4h	comment	Confidence error bars and “central point”: Should we emphasize the median? @whuber After I wrote the edit, I realized that I was looking at it all wrong. Indeed I got away from the definition of the CI and was confusing the distribution of the parameter and the distribution of the repeated estimate of that parameter. Thanks for setting me back on track.
5h	accepted	Confidence error bars and “central point”: Should we emphasize the median?
5h	comment	Confidence error bars and “central point”: Should we emphasize the median? @whuber: I realized that a few minutes after I submitted the edit. I think it clicked.
5h	comment	Confidence error bars and “central point”: Should we emphasize the median? I did my best to clarify in the body of the question. @whuber: confidence limits are defined much more like the median than the mean, which is why I bring median into the discussion in the first place. As confidence goes to 0, the confidence interval goes to a median value (which is also the mean, when the distribution is symmetrical e.g. normal). Perhaps I am making a mistake in trying to push concepts easily understood in symmetrical distributions into asymmetric ones.
5h	revised	Confidence error bars and “central point”: Should we emphasize the median? added context to question per discussion, made equations easier to read.
9h	asked	Confidence error bars and “central point”: Should we emphasize the median?
2d	comment	What does the Scale parameter mean in linear regression? Does this apply to models that don't use probit or logit? My example specifically uses two continuous variables. Does scale still just account for heteroscedasticity?
May 17	asked	What does the Scale parameter mean in linear regression?
May 15	awarded	Commentator
May 15	comment	What are common statistical sins? I try to be statistically literate and still fall for this one from time to time. What are the alternatives? Change your model so the old null becomes $H_1$? The only other option I can think of is power your study enough that a failure to reject the null is in practice close enough to confirming the null. E.g. if you want to make sure that adding a reagent to your cells won't kill off more than 2% of them, power to a satisfactory false negative rate.
May 15	comment	Nonlinear regression: Confidence intervals on transformed or untransformed parameters? Oh, ok. So this answer is applicable in this case but not necessarily in the generalized case. Got it. On reading up more on the lognormal distribution, it seems that even method 2 isn't the best way to do it, but it's a lot better than method 1. That's answer enough for me- thanks for your help.
May 15	accepted	Nonlinear regression: Confidence intervals on transformed or untransformed parameters?
May 14	comment	Nonlinear regression: Confidence intervals on transformed or untransformed parameters? By symmetrical, you mean the variance of $y$ is symmetrical around the mean of $y$, correct? In the generalized case where this is true, is the uncertainty of each parameter also symmetrical around the prediction of that parameter? If that's true, then what you say makes perfect sense.
May 13	asked	Nonlinear regression: Confidence intervals on transformed or untransformed parameters?
May 8	comment	Possible to create random slope model with fixed intercept in SPSS? Can you give a little more context as to what you're trying to do? Are you sure you need to be using the linear mixed model procedure?
May 4	revised	Test regression parameter against a constant in SPSS added 412 characters in body
May 4	asked	Test regression parameter against a constant in SPSS
Nov 12	comment	How do I do nonlinear generalized estimating equations in SPSS If I am reading various online resources correctly, difference-in-difference is just another term for multilevel regression. I know that I can do this with SPSS's Generalized Linear Regression procedure (or even a carefully planned non-linear regression in certain circumstances) but these aren't the same as GEE unless I am doing linear regression (which I am not).
Nov 7	awarded	Promoter
Oct 22	asked	How do I do nonlinear generalized estimating equations in SPSS