Is there COUNTIFS function of excel in SPSS? If yes , please explain the syntax.?

Hello!

Can you help me with this, please?

I have eight numeric variables with codes (1 thru 180, labeling persons). Any code can appear in any variable, once or more. I would like to know, for eg. #4 how many times appear in all (!) of these eight variables.

Simple frequency analysis doesn't work because that tells me only the frequency of the codes separately in the variables. But I would like to sum it up.

Can I do it in SPSS or better in Excel?

Thank you!

Have a nice day,

Mark

I only need 14 variables from a very large SPSS database. I want to create a new databased that only includes the selected 14 variables. I have done this in the past but I can't remember how I did it. Any help would be greatly appreciated.

Hi, I am new on SPSS, I hope you can provide some insights on the following. I have a data base of patients which contain multiple variables as yes=1, no=0. I want to work on this data based on multiple cases selection or subgroups, e.g. patients with variable 1 (1) which don't have variable 2 (0), but has variable 3 (1) and variable 4 (1). Variable 4 includes selected patients from the previous variables based on the output. In other words, let’s imagine we have a database from 10000 patients with crohn’s disease, I want to select ulcer location (loc-1, loc-2, loc3 and loc-4), for later comparison. However, the patients, based on ulcer location, should also be subclassifed as patients with hyperglycemia (1), which also have skin rash (1) and received corticosteroids (1). After I would later compare the same selected group with patients with hyperglycemia (1), which also have skin rash (1) and did not received corticosteroids (0). How can I do it using SPSS? I think you have to use the select cases tool, but I don’t know how to select cases (or variables) upon cases (or variables). Thank you very much in advance.

Hi,

I would like to compute a binary (yes/no) variable using the conditions of two categorical variables, i.e., a score of 0 or 1 on one variable and a score of 2 on another.

How do I do this? I have tried using the 'if' function but cannot seem to ensure it satisfies both conditions at the same time.

Thanks,

Esther

Let's say I have three variables in SPSS, each being answered on a Likert Scale of 1-5 (little to much):

How much do you enjoy chocolate ice cream?

How much do you enjoy strawberry ice cream?

How much do you enjoy vanilla ice cream?

Say I want to, for each case, select the highest value of the three aforementioned variables and recode that into a new variable (to indicate the maximum level of ice cream enjoyment). Is there a way I can do this using a syntax in SPSS?

like in stata how one may replace for missin values ussually given by a (.) into something like 0

Hello,

I have recently created a multiple response set from a check all that apply question. I see that I can compute frequencies for that response set, but is there a way to use the new response set as a variable for other inferential analyses? For example, a linear regression? If not, is there a better way to handle my check all that apply question that would allow for future analyses like regressions?

Thank you!

I am doing a panel data analysis in R Software which is truncated with more than 700 firms and a 20 year sample period. While using the "trunc" option in the pldv function, it gives this error:

modelo <- pldv(loss_amount ~ roa + roe + lev_ratio + unem_rate + hpi + inflation + rule_law + pol_stab + reg_qual , data=Dataset, index=c("firm", "year"), sample = c("trunc"))

I checked the correlations between variables and there is no issues with the variables used in this regression. I also checked for collinearity using VIF and Tolerance and I found issues for 2 variables, which were deleted from the model.

If I change from "trunc" to "cens" option, it gives no error, which is strange. How can I solve the issue?

NOTE: I attached a sample of the data I am using

The data of my research consists of 5 independent variables and 1 dependent variable. After running multiple linear regression in SPSS it is found that the beta coefficients of 2 independent variables are negative while 3 independent variables have positive beta coefficients.