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Interpretation of Little's MCAR (missing completely at random) test and how to go on

My Little's MCAR (missing completely at random) test on 12 items revealed chi-square = 138.281, DF = 84, and sig. = .000. (SPSS Output) I wonder if I can conclude that the data were not missing ...
user2314's user avatar
0 votes
1 answer
236 views

Conditions to Select Pairwise Deletion

When should I select pairwise deletion? So I grasp the idea of pairwise deletion, but what conditions are actually needed to select this? Is it when data is MCAR? Why would researches select this ...
Fats's user avatar
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-1 votes
1 answer
76 views

Question about MCAR, MAR and MNAR

I have 3 datasets. Each of the three datasets “data1.csv”, “data2.csv”, “data3.csv” is about the same sample of 654. (I imported the datasets in R studio.) subjects: youths, aged 3 to 19 with the ...
Chiara Gobbi's user avatar
0 votes
1 answer
116 views

Missing at Random vs Missing Completely at Random

From what I understood: MCAR - missingness do not depend on the values of Y (observed or missed) MAR - missingness depends only on the components of Y that are observed, and not on the components that ...
Tiago Dias's user avatar
1 vote
0 answers
29 views

How to identify whether my data follows "Missing At Random" (MAR) mechanism or not? [closed]

I was having two similar studies with two variables (anti-gE and anti-VZV (continuous variable)) linearly related to each other (with same relationship between both the studies in anti-gE and anti-VZV)...
PRASANNA's user avatar
0 votes
1 answer
1k views

Little's MCAR test Chi-Square =.000

I am trying to understand the results of my Little's MCAR test (SPSS 26). Chi-Square = .000, DF = 2113, Sig. = 1.000 As much as I have read articles reporting Little's MCAR test, nobody reports Chi-...
Sirkake Liisuke's user avatar
2 votes
2 answers
94 views

Dataset having about 1% missing fraction, missing completely at random. How would I address the missingness of the dataset?

I have a dataset comprising of 1% missing fraction where data is missing completely at random. How would I address the missingness of the dataset with a multiple imputation technique? For example, is ...
Matt.W's user avatar
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2 votes
1 answer
67 views

Is data that has been entered incorrectly treated the same as missing data?

I am doing an online study and have just started looking at the data. I noticed two of my participants have listed ages that they couldn't possibly be (e.g 450 and 220). I'm wondering what the ...
Riss's user avatar
  • 21
2 votes
1 answer
261 views

MCAR, MAR and EM

I have a binary(1/0) classification task. I am trying to find $p(y = 1 | X)$ where $X$ is the vector of input variables and $y$ is the binary output label. Suppose that for some records the output ...
Cagdas Ozgenc's user avatar
0 votes
0 answers
32 views

All items missing for various questionnaires

this is actually the first time I'm working on a big dataset and I really hope someone can give me some advice on how to handle missing data. I tried to find information regarding my problem but can't ...
Corinna Zink's user avatar
1 vote
1 answer
159 views

MCAR NA imputation

I would like to create a MCAR database in R from an existing complete one. I would like to have only some variables with NA observations, here's the code I used: ...
ArTu's user avatar
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4 votes
1 answer
2k views

MCAR test for large number variables and small sample size

I have a dataset with 101 observations and 402 columns (those columns comprise several multiple-item questionnaires). Among those 402 columns, 10 of them are categorical and the remaining are ...
adonies's user avatar
  • 115
0 votes
1 answer
535 views

How to test that your missing data is completely at random (MCAR)

I am doing a secondary analysis of data from a local trial (N=450, mean follow-up longer than 10 years). I am specifically looking at a secondary outcome (diagnosis of hypertension) after 10 years ...
Vincent's user avatar
  • 263
1 vote
0 answers
119 views

Adjusting n after using pairwise deletion

I am using pairwise deletion to compute the correlation matrix of a data set. I think this approach is appropriate because: I have well under 10% missing values (~2%) I have only around 50% complete ...
bmrn's user avatar
  • 111
1 vote
2 answers
992 views

Little's MCAR test: why must missing values be random?

When we have data with a lot of missing values, as I see it, the missing values are likely to be observed with some systematic properties. Maybe some sex is more likely to not answer a question and ...
Erosennin's user avatar
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0 answers
789 views

What to do when expectation maximization results are invalid (they don't match the likert scale)

I have missing values (MCAR) for which I used EM to fill in those values. Some of the imputed values are negative integers or zero. I am using a likert scale to measure responses, and thus i need the ...
Northerntravel's user avatar
2 votes
1 answer
18 views

should you include DV in MCAR when missings are found in IVs?

can anyone please help me with this question, can't find a satisfactory answer on the stats sites. A reviewer of one of my articles commented that I should include the DVs in my MCAR analysis. But i ...
Joan's user avatar
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4 votes
3 answers
11k views

How to interpret MCAR (missing completely at random) any papers that I can read?

When dealing with missing data and Little's missing completely at random test, it's widely considered that if the test has a significance level of P>0.05 the data can be considered as MCAR. But, I ...
Pretty_Girl's user avatar