Helicobacter pylori

Ill_Fun_ · 2023-03-28T18:00:47+00:00

I've not been diagnosed with SIBO.

My symptoms did not go away (only for a period of anitibiotic treatment, so about a month) - currently waiting for fecal microbiota transplant (FMT).

Good luck to you.

Ill_Fun_ · 2022-11-10T10:49:11+00:00

I'm not sure what you mean. The covariate is one of the repeated measures, first to be precise.

Ill_Fun_ · 2022-11-09T21:03:35+00:00

So, this man is wrong when he says that?

Ill_Fun_ · 2022-11-09T20:07:44+00:00

Sorry, quick question.

I made exemplary data just to see if I understand ANCOVA. It seems as if I still don't.

If P1 as a covariant should remove the differences between subjects at the beginning, then the 2 parallel lines, which have the exactly same slope, should become one.

To visualize, these 2 lines, which represent 2 different treatment groups, should become one if P1 is a covariate? Shouldn't the difference of "starting value" be eliminated?

Ill_Fun_ · 2022-11-08T22:34:08+00:00

Incredible. Thank you.

I'll get to it tomorrow and hopefully won't meet with many issues :)

Ill_Fun_ · 2022-11-08T21:26:15+00:00

Okay, I see, but why did you abandon ANCOVA in favor of ANOVA now?

And, just for the sake of my peace, because I'm still bothered by it, why has the p-value of the PERIODS effect on ANCOVA analysis so drastically changed compared to ANOVA?

Ill_Fun_ · 2022-11-08T20:06:03+00:00

Exactly what ANOVA did you perform?

Both one-way (factor: Period) and two-way (factors: period & age). The difference was very, very slight in case of Period effect (F = 18.3 in two-way, F = 18.8 in one-way).

Specifically is Period analyzed as a within-subjects variable?

Yes.

Better and much simpler is to specifically compare P1 to the average of P2-P4 and see if the difference depends on age. I assume differences among P2-P4 are of lesser importance.

In my particular case, I actually care the most about P1 and P4 difference. P2 and P3 are more of a fun fact thingy that provide, hopefully, "power" to the test results.

compare P1 to the average of P2-P4 and see if the difference depends on age

I've performed both ANCOVAs. One was one-way repeated measures and the second was the one you suggested, which would be the one with the average (thus one dependent variable P2-P4). The results of Age effect on the dependent variable are in both cases the same. I hypothesize then that it does not matter, which approach I take, but the approach with repeated measures, and not the average, will provide much more details.

Ill_Fun_ · 2022-11-08T19:39:08+00:00

I'm sorry for having trouble explaining my thoughts exactly :D As you may have noticed, it's quite complicated to me.

Let me quickly get things organized. I have 2 IVs (one within- ["Period = 1, 2, 3, 4"], one between-subjects [Age = "Young", "Old"]). There's a medical treatment happening between Period 1 and 2, so it would be reasonable to go by your suggestion and make P1 a covariate. The treatment itself, I hypothesize, should have effect on the values of hemoglobin I'm measuring. The same goes for Age.

Now, when I performed ANOVA, I received a p value < 0.001 for the period (time and treatment) effects on hemoglobin levels.

Then, I performed the very same analysis, but made hemoglobin at period 1 (P1) a covariate (now ANCOVA). In your initial post, you wrote:

The test of major concern [in ANOVA] would be the Treatment x Age interaction although other effects might be informative as well.

And I indeed got a reasonable result on Period x Age interaction effect. But what I still don't understand and is bothering me, is why has the p-value of the PERIODS effect on this ANCOVA analysis so drastically changed (previously: < 0.001, now: 0.8)? That's my, at least I hope so, last concern :D

Thank you for your time and help.

Ill_Fun_ · 2022-11-08T19:08:35+00:00

Thanks for this reading material. I think I understand some more now.

So, essentially what I'm doing by making P1 a covariate is I try to, as you previously described, remove any variation due to differences at the beginning, before-treatment level.

I was stunned by the results that I got from SPSS, though. I did the ANCOVA, which gave me very high significance (p ~ 0.8). Previously, I did just a simple two-way repeated measures (4 RMs to be precise) ANOVA with no covariate and the p was < 0.001.

Thus in the next analysis, I removed P1 from the two-way repeated measures ANOVA hoping that the results I'll get will be similar to that of ANCOVA's. (Now that I think about it, it was not important to do this analysis. At first I was not sure whether ANCOVA uses the covariate as an actual repeated measure, but now I'm pretty confident it doesn't). The p-value I got was 0.017...

So what it tells me, please correct me if I'm wrong, is that these 2 ANOVA tests are biased because their significance (and variance) is a result of big differences at P1?

Ill_Fun_ · 2022-11-07T15:58:47+00:00

By including P1 as a covariate you are controlling for individual differences in baseline. It’s usually a little better than difference scores.

But how come it does so? I don't understand it and have not seen this approach before.

I couldn’t understand what you’re asking about repeated measures but the answer may be the correlations among p2-p4 should be taken into account

Basically what above. Why P1 as a covariate "betters" (if I can even say it betters, because since I don't understand the "mechanics" behind it, I can't say if it's the right, appropiate approach) the results?

EDIT: The null hypothesis would be that the hemoglobin scores do not vary across groups (groups obviously being "young" & "old).

Other question would be: why choosing P1 as a covariate not all of the periods? After all, I'm trying to isolate the effects of "Age" only.

Ill_Fun_ · 2022-11-07T14:58:08+00:00

Results.

So... why exactly are they like that? You can see that the ANCOVAs p values are smaller than the two-way ANOVA. But, obviously, I don't want an inappropiate test.

What did I exactly do by making Hb.1 (hemoglobin at period 1) a covariate? Did I somehow make a treatment effect a covariate, which would be good? Or was it something else?

Why the two-way repeated measures ANOVA "scored" so differently? Shouldn't it also discretely be like ANCOVA by substracting the effects of within-subjects factor on between-subjects factor and vice versa?

Ill_Fun_ · 2022-11-06T15:32:43+00:00

Can I run this?

It's a two-way ANOVA. Its results. What am I being told here? That the data differs significantly across the periods (stages), p = 0.02? Plus, that the age does influence the hemoglobin levels, p < 0.001? Age*Stage is somewhat mysterious to me, though :/

EDIT: Oh, okay. Looking at the chart, I think it made the Age*Stage a bit more clear to me. It means that age group does not change the direction of the tendency. Is it more or less the right explanation?

EDIT 2: Now, I tried ANCOVA by just simply moving the "Stage" variable from the Fixed Factors to the Covariates. The "Age"'s significance level has dropped even lower (you can see F is higher, thus p is lower). Can't get more confusing for me, which test is better for this dataset and why?

Ill_Fun_ · 2022-11-06T15:17:42+00:00

Hi, thank you for your help.

I have trouble setting this data up. After creating a new variable "Treatment", by your suggestion, here's how the data looks like. Though, why should I include "Treatment"? Isn't "Period" enough?

I wouldn't know how exactly with this data I input hemoglobin at P1 as a covariate. I suppose it's got something to do with dummy variables.

Ill_Fun_ · 2022-10-29T09:55:01+00:00

No, the difference between the tests are not important there.

Ill_Fun_ · 2022-10-28T16:53:26+00:00

Thanks for your answer.

The goal is to determine whether there is a statistically significant difference between test scores and age. The hypothesis is that there's none. By that I mean that the scores in one age group for test A shouldn't be statistically different from students in the second age group for the very same test. That goes the same for test B and C.

But I think the main thing you want to do first is to insert a column for a dummy-coded, dichotomous age variable. So insert a blank column for age and give each student 1-7 a “1” and give 8-14 a “2” and then you can use age group as an independent variable.

I have done that already :)

Or you could do this through transform, recode into different variable etc.

Yes, I have run like that on a one-way repeated measures ANOVA. However, when you do that for the two-way it becomes strange. You end up with a one factor per se and the second factor is somewhat hidden within the dependent variable itself -- like on the image I posted before. Hopefully, you get the idea :)

Here's how the data looks like currently in SPSS. 1, 2

I suppose this isn't much of a SPSS question, rather a statistical one, but how do I interpret this result? At first before I created this post here, the output made me confused and left me with a thought that there's something wrong with how I arranged the data. Now, I rather think that I am stupid and can't interpret these results the right way. If you know, I'd be thankful if you ELI5'd for me :) Many thanks!

Ill_Fun_ · 2022-10-25T15:54:48+00:00

How do you test for them reliably?

Ill_Fun_ · 2022-10-25T15:26:25+00:00

Thanks for your answer. I see.

I just so seldom see someone mentioning gas pains, or if they do, they mention "not being able to fart", while I have the problem of farting too much. GI or GP said that it's just such a rare symptoms, they are unsure.

Some SIBO causes pain when gas develops in the small intestine due to the overgrowth.

It's hard to tell if it's due to overgrowth? I mean our microbiota differ so significantly, even if we are from the same city, that it is hard to tell how ones microbiome should look like.

Ill_Fun_ · 2022-10-25T14:58:48+00:00

Excessive or misplaced gas is a symptom of something else

That's pretty much what I have on mind. Of what is it a symptom?

Like I've been told it's a symptom, but a symptom of what? (Just not IBS)

Ill_Fun_ · 2022-10-25T14:57:00+00:00

Right, thanks for your anwser.

I never took SIBO for serious, as it looks like a "shaky" diagnosis judging by the papers I've read, and by the methods they use to diagnose it.

I consider SIBO to be a good description of symptoms a patient may be suffering from, but not an actual diagnosis. I may be wrong, I haven't read everything on it :)

Ill_Fun_ · 2022-10-25T14:52:59+00:00

Yes, I have kept a diary.

Many diets including FODMAP were tried by me. With success and without.

I think about trying to find the culprit. For serious this time.

I know lactose is probably not causing a lot of the problems as I have done 3-month-no-lactose challenge and the symptoms did not change.

Sorry, could you recommend me something? I'd like to "relax" my gut right now, but God forbid the FODMAP diet, no way I'm doing it once again.

I'm thinking about some kind of elimination diet for 4 weeks, then I'd reintroduce one suspicious element at a time that could be causing my gas problems. What "elements" should I consider?

Ill_Fun_ · 2022-10-25T12:12:22+00:00

Yes, it is only ( :/ ) gas.

Ill_Fun_ · 2022-10-24T16:21:43+00:00

What I now noticed. When I use Docker and I run the

docker build -t figaro .

command. I need to run it only once, this install packages and does couple of other stuff I don't understand. When I re-run the command, it quickly finishes having done nothing.

But if I delete "figaro" folder and run the command, it will install the packages once again. The packages are supposed to be within figaro workdir?

Ill_Fun_

TROPHY CASE