Hello, my statistics is very bad so im not sure if I understand it right.is this always a way if we want to pairwise after Chisqare test? I have 5 kinds of animals and i want to see if they are different in where they are found. so i have 5 animals and 5 locations, i used chisquare and have gotten that p-value < 2.2e-16. but then i wanted to see which 2 animals are different from each other, in this case can i also use residuals in R...? becuase it doesnt seem right thank you!
The residuals post-hoc looks at a single cell and if the value is significantly different from what would be expected, not if it is significantly different from another cell. You might be more interested in a column proportion post-hoc test. Unfortunately I haven't made a video on this yet. It is available in my stikpetR library: install.packages("devtools") devtools::install_github("stikpet/stikpetR") library(stikpetR) You can then run the function ph_column_proportion(field1, field2). I have the same function in my Python stikpetP library, for which the documentation is found at: peterstatistics.com/Packages/python-docs/other/poho_column_proportion.html Hope this helps.
@@stikpet and I would like to ask if I have multiple categories in both variables (unlike yours only female and male), is Bonferroni adjustment enough? or is there any other correction/adjustment I would need to do. thank you very much!
Bonferroni adjust for the number of tests performed. The residuals are based on the cell, so a test for each cell, with more columns you use more cells so that increases, the principal stays the same if you use 2 or 200 columns, just a lot more cells and therefor more tests.
I followed this exactly and even did the copy paste for the value labels and it still says it can't generate the table and says this: TABLE: The category labels cannot be repositioned because the value labels of several categorical variables conflict with each other. I dont understand what I can do differently to fix this
strange. Just tested it myself again in SPSS version 29 and this should still work. Hard to tell what the problem might be without being able to replicate the error. Perhaps you can send me the file?
I know I'm very late and actually new in this. In this video, did we use a, b and c superscript to the significant group, or just a and b? How do we know both is different each other? Thanks in advance
it's the value to enter if someone for example skipped the question. The 999 is just my own choice, you can chose any value you like, or leave it blank. I explain it in this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-2cDujlIDXgc.html , or on my site at peterstatistics.com/CrashCourse/SPSS/SPSS-2.html. Hope this helps.
If you use the chart builder, you can set the order of the X-axis. At about 2:20 in the video you can see the 'Sort by' option of the X-axis. If you set it to 'value' it will sort them alphabetical. You could also first automatic recode the category variable (Index1) using Transform - Automatic recode from the menu bar, then use this new recoded variable. This will make it possible to sort the X-axis in any order you want. Hope this helps.
@@stikpet Thank you so much for your reply!! I have a gene expression as a continues values (50,28,49...) and a parameter as a nominal (0-1). When I try to do one-way anova and post-hoc in SPSS. It says Warnings Post hoc tests are not performed for Hao1_Median because there are fewer than three groups. Any idea about this? :(
strange, I thought I replied already. Anyway, simplified the one-way ANOVA determines if any of the means in the different categories could be different from each other. If at least one differs from another one a post-hoc analysis could determine which ones are different. Now if the one-way ANOVA is not significant, there is no point to perform a post-hoc analysis, there is also no point if there are only two groups (since if there are differences it can only be between those two). It seems you have only two categories (0 or 1), so no need for a post-hoc analysis. Actually the one-way ANOVA is then the same as an independent samples t-test. See for more info on this: peterstatistics.com/CrashCourse/3-TwoVarUnpair/BinScale/BinScale-T-test(independent%20samples).html
The ols function have in their documentation "Model statistics are given in the order of args.", so it is not the one/two/multi-way anova but the number of arguments. For a one-way ANOVA you need two: one that specifies the groups, and one that specifies the scores.
the official answer is always: it depends on the field you work in and you should not use rules of thumb. I always find that a bit unsatisfying, since not everyone is an expert in the field or has seen enough situations to know about this. Many rules of thumb find their origin in Cohen (1988). Cohen has a formula to convert eta-squared to Cohen f, and has some rule of thumb for Cohen f. I've done the conversions already and posted the rule-of-thumb interpertation at peterstatistics.com/CrashCourse/3-TwoVarUnpair/NomScale/NomScale3c.html. Hope this helps.
What if I need p value for each row, for example Hypertension (Yes and No-Row) vs Sex (M & Female) I need P value for both Yes and No - p value for each row How to do please
Not sure if seeing the actual p-values is possible with SPSS for this post-hoc analysis. I do have I think something on how to do this with R, Excel or Python if you are interested.
@@SonikaYadav-gy6pm as the names imply they show the first shows the results of the independent samples t-test (and the Levene test for variances) and the other the effect sizes calculated. Each column shows something else which might be of interest. In the first table usually the p-value (sig.) is the most important. You can find out more about the test on my website.
hey mate, great video! I've a question, is it possible to do a kruskal wallis with two groups? I want to know the interaction between groups and i cannot find anywhere.
A + or - value occurs due to the t-value from the test. In turn this t-value is + or - based on the numerator in that calculation. This is usually average of before - average of after. This will be negative if the average of after is greater than the average of before.
Thank you! Can you suggest how I should do my analysis? I have a nominal variable with three categories (attitudes - positive, neutral, negative) and an ordinal variable with three or four categories. And some values lower than 5, some even 0.
for nominal-ordinal usually a Kruskal-Wallis test is recommended, but your nominal variable seems with 'positve-neutral-negative' more ordinal. On my website (PeterStatistics.com) you can see which test I recommend for which combination of variables, and links to my youtube video on how to perform those tests. on a side note I almost reported you since my phone cut off your message and first didn't see the part 'ysis? I have a nominal....' 😁
if you select all the output, then right-click and select 'Export' you get the option to save the output as a Word document. You can then convert this Word document to a pdf.
thanks for the tip. Never knew about the aggregate function. Quite interesting how you can also use it to ignore hidden rows. For anyone else interested the microsoft help page is actually helpful: support.microsoft.com/en-us/office/aggregate-function-43b9278e-6aa7-4f17-92b6-e19993fa26df
Hi Stikpet, Great video. Do you by any chance know, how we can calculate the joint CDF in higher dimension (let's say five random variables). My students are not familiar with programming languages, so I would like to stay in Excel, and the application is financial in the way of Gekse's (1978) compound option theorem. Do you have an e-mail I can write to you on?
oof, the bivariate normal was already quite a lot of work to figure out, and unfortunately never dug deeper to the multivariate version (which you probably need). My email is simply my youtube channel name with gmail.com :-).
I'm not sure which version this was. The video is 7 years old, so I guess it was version 24 or 25. I'm currently using version 29 and this should still work. Also the documentation of version 27 mentions the method shown (www.ibm.com/docs/en/spss-statistics/27.0.0?topic=sets-defining-multiple-response).
sorry for the late reply. I'm not sure if this is possible using this method. However, if you create a cross table, including the total you can 'convert' the table into a clustered bar chart which should than have the result you are looking for. A video on how to convert a table to bar-chart can be found at: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-tO8CS2DWGSE.htmlsi=IYbTtDuu6SQ45u5B
sorry for the late reply. I'm not sure if this is possible using this method. However, if you create a cross table, including the total you can 'convert' the table into a clustered bar chart which should than have the result you are looking for. A video on how to convert a table to bar-chart can be found at: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-tO8CS2DWGSE.htmlsi=IYbTtDuu6SQ45u5B
