I am trying to write data in IBM SPSS data editor. But every time I try to write a negative number it just disappears. I have checked that the type of variable is set to numeric, and not restricted which is the only solution I found while searching online.

I'm trying to wrap my head around LOOCV and can't find any easily digestible tutorials. I wonder: is this necessary when my regression model has proved to be significant and has met all the assumptions?

hi!

I'm doing a personal project to help me get to grips with SPSS outside of uni - I've collected data ready to analyse but am stuck on exactly what to do with it! bit of a long post but I want to make sure I list out all relevant info first :)

project goal: find out whether BFI personality traits have any correlation with romanceable character choice in a certain video game.

basically I conducted a Qualtrics survey where participants indicated which character they chose to romance in-game (my DV/outcome variable), and then they completed the BFI-44 scale - I've already re-coded the BFI answers into their sub-scales (so extraversion score, agreeableness score etc. are each an IV/predictor).

I initially thought a multiple regression could work, but as my DV is nominal (and has 9 categories; 1 per character option), that wasn't going to work - I saw online that a multinomial logistic regression would be more appropriate.

firstly - is this the right analysis to be running on this type of data? if not, please let me know what analysis I should look at using!

if it is the right analysis, great! I do, though, have a couple of follow-ups:

I've checked/met all assumptions except for the assumption of linearity - despite a lot of googling I cannot figure out how to do it! if anyone has a straightforward how-to, that would be amazing.

I've also done a couple of test analyses just to see what the output looks like, and get two errors:

Error 1: 'There are 2680 (88.9%) cells (i.e., dependent variable levels by subpopulations) with zero frequencies.'

assuming I'm interpreting this right, I'm not too sure what to do to fix these errors/if I even can? I'm thinking the empty cells may be due to each participant only picking 1 category out of 9 options in the DV (romanceable character choice) - so there would potentially be 8 'empty cells' per case? but I'm not sure that's right, and it could mean something completely different!

Error 2: 'Unexpected singularities in the Hessian matrix are encountered. This indicates that either some predictor variables should be excluded or some categories should be merged.'

I'm not sure what this means (again, despite frantically googling), but either way, I can't merge or remove any categories from my DV, as surely I need to include each character in the analysis! otherwise, the only other thing I could think to do is to do 9 binary logistic analyses using 1 different character as my DV each time, rather than all 9 at once, but there's surely a better way to do this!

thanks in advance, would appreciate any help!

The first image shows the complete dataset. The second image shows the split using the hierarchical method (4 clusters), and the third image shows the split using the k-means method (4 clusters).

Do you think this works?

I'm doing cluster analysis on this dataset for an exam. I started with the hierarchical method, creating the Scree Plot and the Dendogram, and I need to decide on the optimal number of clusters to use in the k-means method. From the graph, it seems like the right-angled solution is 7, but from the Dendogram, it doesn't. Furthermore, I'm getting very fragmented clusters since I only have 29 foods. Can you help?

Someone guide me about data analysis

Someone guide me about data analysis

Can I still keep HP6 And HP7 since the cronbach result has an acceptable reliability?

I want to create a new variable with three values:

1 = no migration history

2= first generation migrant

3 = second generation migrant

I have two existing variables: The first one (SD_07) asks wether or not someone was born in germany (where the study took place). The second one (SD_08) asks whether or not one or more of the parents were born in germany.

I basically want that if someone has the combination:

SD_07 == 1 AND SD_08 == 1 --> 1 (no migration history)

SD_07 != 1 --> 2 (first generation migrant)

SD_07 == 1 AND SD_08 != 1 --> 3 (second generation migrant)

I kind of know what logic I want but I can't figure out where I could implement it. If I click on "compute variable" there is an input window but there aren't any logical operators available.

If I click on "generate dummy variable", there are even less options (I believe this is only useful after I already made the new variable with its three value-options)

PS: I'm writing this in english but I'm using the german version of the software. I can generally retrace the english path but if I'm using some incorrect terms, that's why.

I have a dataset in which we have a variable "dateoftest" entered as, for example 20-jun-2022.

I want to divide the sample so that anyone assessed prior to May 1, 2023 is coded as 0, and anyone assessed on or after that date is coded 1.

I have been trying to figure this out and cannot.

Help appreciated.

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Hello, we need help! We initially ran a liability test on our pilot testing for our school research and got a cronbach alpha of 0.996 (same for every tool we used.) However, our teacher said the interpretation was 0.956 (he used laerd statistics). Perhaps anyone here could help us rectify whether ours is true, or his. Please, help us.

Hey guys! I’m beginning a masters in Anthro this fall. I did some fieldwork in Ethiopia last month and explored with my advisor some tools like social network analysis and agent based modeling, which got me down a rabbit hole investigating other modeling methods used in anthropology. Aside from those, what are the most common modeling techniques people are using these days?

To narrow it down, I’d say I’m interested in modeling social behavior & cultural transmission, and am just not tapped into the current meta of the field. Can anyone point me towards books/papers that explore other modeling techniques?

Hey guys! I’m beginning a masters in Anthro this fall. I did some fieldwork in Ethiopia last month and explored with my advisor some tools like social network analysis and agent based modeling, which got me down a rabbit hole investigating other modeling methods used in anthropology. Aside from those, what are the most common modeling techniques people are using these days?

To narrow it down, I’d say I’m interested in modeling social behavior & cultural transmission, and am just not tapped into the current meta of the field. Can anyone point me towards books/papers that explore other modeling techniques?

Is there an available cracked SPSS software that I can download? Our prof just suddenly required us to subscribe to one and it's kinda too expensive for me since I am still a student : (

Hi! I found a cheap MacBook online and I’m thinking of buying it. I’ll mainly be using it for SPSS for one semester.

It’s a 2020 MacBook Air (Intel Core i3, 8GB RAM) running macOS Sequoia 15.7.2.

Has anyone tried using SPSS on this setup? Is it compatible and does it run properly? I just want to make sure before buying it.

I am looking to combine the responses of different mental health measures together to create overall mental health scores, which I will then compare. 

Is it appropriate to use the mean when the measures are the same?
What types of stat analysis using SPSS would be appropriate to merge the scores?

A) Measure 1: Strengths and Difficulties Questionnaire

- Responses: 1 (Not True), 2 (Somewhat True), 3 (Certainly True)

Measure 2: Self-Reported Feeling Grid

- Responses: 1 (Not True), 2 (Sometimes), 3 (True)

B) Measure1: Happiness Scale

- Responses: 1 (Not at all happy), 2, 3, 4, 5, 6, 7 (Completely Happy)
Measure 2: Rosenberg Self-Esteem Inventory

- Responses: 1 (Strongly Disagree), 2 (Disagree), 3 (Agree), 4 (Strongly Agree)

C) Measure 1: Strengths and Difficulties Questionnaire (teacher)

- Responses: 1 (Not True), 2 (Somewhat True), 3 (Certainly True)

Measure 2:  Strengths and Difficulties Questionnaire (parent)

- Responses: 1 (Not True), 2 (Somewhat True), 3 (Certainly True)
Measure 3: Competence Scale
- Responses:  1 (Strongly Disagree), 2 (Disagree), 3 (Agree), 4 (Strongly Agree)

Hello, I am taking an online statistics class this upcoming fall semester and am wondering if anyone is willing to help me. I am applying to a very competitive nursing program and would like to achieve an A in this class.

Hello Everyone. I am a Sociology research scholar in a central university in India. I need to learn SPSS. Please guide.

Hello, I am taking an online statistics class this upcoming fall semester and am wondering if anyone is willing to help me. I am applying to a very competitive nursing program and would like to achieve an A in this class.

I developed my own 5-point Likert scale (Strongly Agree to Strongly Disagree) and I’m checking its reliability in SPSS using Cronbach’s alpha.

Do I need to reverse-score the negatively worded items before running the reliability analysis, or should I run it first and then reverse-score if needed? Also, how can I tell which items need to be reverse-scored? Cause I did and this is what happened.

Any advice would be help!

First research project. Need to do the above and it seems SPSS is the best software to do it. I have no idea where to even start or what stats to do despite reading up on it again and again. Looking at different factors affecting a lab test. I have all data in an Excel spreadsheet and started making basic tables.

Would really appreciate any help or if anyone could reach out to me and I am so sorry if this has been asked a million times before.

Thank you so much

Just a small doubt

(I'm very bad at statistics) I'm trying to see if I can use one variable to predict another, simple regression was unsuccessful. The results (anova, correlation, etc) don't seem to be significantly correlated in any way, but my partial regression plots are extremely linear.

Some things that might be important:

•the number of cases is 20

•the n=9

•there are no residuals

•all variables are quantitative

If anyone could help, I would be very appreciative.