Thank you so much for detecting that error! It works now! ... View more

Thank you so much for detecting that error! It works now! ... View more

Hi,   Thank you so much for clarifying the root cause of my SAS issue. I have already concatenated the two folders into a single library and was able to view all datasets located in both folders. Thanks again! ... View more

Hi,    Thank you for suggesting the "sas concatenated library" as an alternative solution to the SAS issue. I will definitely google the specific details involved in this procedure. ... View more

Hi Suryakiran,   So, I have just tried to run each SAS code separately instead of both codes simultaneously. When I ran the first set of SAS codes, I am able to see all of the SAS datasets from my first folder within the SAS library. However, when I ran the second set of SAS codes, the datasets from the second folder overrode those from the first folder. Perhaps I should create two different libraries?  ... View more

Hi Paige,   Yes, I definitely think that inconsistent data in certain categories may be another major reason for the observed wide confidence intervals. Thank you again!   Best,  Lisa ... View more

Hi Paige,   Yes, I am employing survey-based binary logistic regression models for the categorical variables in my dataset. Nevertheless, I have not observed any extraneous categories within the either the independent or dependent outcome variable although there are some missing values within both variables.    Regarding my previous questions, I would just like to know whether there may be some alternative explanations for those significant point estimates and relatively larger point estimates for a specific category of the dependent variable but not for the other category. While I have also confirmed the relative sample sizes for each independent/dependent variable category, I was only able to conclude that wider confidence intervals correspond relatively smaller sample sizes since some weighted percentages were greater than 10%.    Best, Lisa ... View more

Hi Paige,    Thank you again for suggesting plausible reasons for the observed wide to extremely wide confidence intervals. However, I would like to seek additional clarification on the possibility of outliers for the categorical variables, in which I have verified based on a descriptive summary statistics analysis that no extraneous category exists. Also, could you perhaps provide some explanations for the observation that certain odds ratio point estimates for exposed group and response group are significant while others for the same exposed group but a different response group are insignificant. I have actually noticed that some of the confidence intervals associated with the significant point estimates are rather narrow, which may indicate relatively larger sample sizes. Nevertheless, I would still like to seek your advice on this observation.   Also, could you possibly attempt to provide some explanations as to another observation in which I observed larger point estimates for the "low/medium" response category but smaller point estimates for the "high" response category. I have noticed that some of the larger point estimates correspond with a slightly wider confidence interval, which may be due to relatively smaller sample sizes. Another possible reason may be that relatively greater odds exist in the "low/medium" response category as opposed to the "high" response category for the same independent exposed group. Yet another rather obvious explanation may be that the log odds ratio estimate is simply higher in the "low/medium" response category with the larger odds ratio point estimate compared to that of the "high" response category with the slightly smaller odds ratio point estimate. Again, I would like to seeks your advice on the stated observations. Thank you!   Best, Lisa ... View more

Hi Paige,   Thank you for providing several possible explanations regarding wide 95% confidence intervals. Since I am only conducting bivariate survey logistic regression using a single categorical predictor and response variable, I do not think that outliers or multi-collinearity would be an issue of concern for my analyses. From my scrutiny of the results of crude odds ratio point estimates and corresponding confidence intervals, it appears that the main reason for the wide to extremely wide confidence intervals may indeed be attributed to relatively small sample sizes within the individual cell of the 2x2 contingency table.   Best, Lisa ... View more

Hi Reeza,   Thank you very much for your suggestions on interpreting the wide confidence intervals. I have just checked the standard error (0.7246) for one odds ratio point estimate (1.82) that corresponds to 95% confidence interval of  (0.44, 7.52), which is slightly larger than the standard errors that I have obtained for those point estimates that correspond with narrower confidence intervals. Moreover, I do not think that I have to standardize logistic regression because once I take the antilog of the log odds ratio (e.g. beta coefficient estimate), the point estimates would revert back to the normal scale, correct? Thus, would it be reasonable to conclude that the wide confidence intervals are due to larger standard errors? Thank you again!   Best, Lisa ... View more

Hi Reeza,   My research group was considering conducting statistical tests such as chi-square tests to determine the association of the selected independent variables and dependent variables. If the p-value is significant (p<0.20 in our case), then we could safely proceed on to conducting logistic regression analyses by using those variables that are associated with each other. Moreover, we have some hypothetical assumptions on the independent variables that are expected to be associated with the dependent variable. Nevertheless, we are actually analyzing secondary survey dataset created by another colleague but did not expect so many cells with 0 frequencies that would not allow for collapsing.    Best, Lisa ... View more

Hi Paige,   Both attachments that I have sent to you are actual data/cross-tabulation output tables that SAS has created based on the statement proc surveyfreq. Unfortunately, the formatting of the text file is rather distorted, which is why you may not be able to clearly see all the 0 frequencies. Since you do not trust the word attachment that I have sent you, I really do not know of another document format that is acceptable and maintains the original formatting of the output tables (perhaps an excel document though).   Actually, I have already received a rather helpful response from another SAS expert, Reeza, that appears to provide the needed solution for that particular cross-tabulation (sex*lang) only. I believe that my research group may have selected infeasible variables to cross-tabulate, which may mean that the research study itself may be infeasible using the current survey dataset.    Nevertheless, I really appreciated your time and assistance on this dilemma.   Best, Lisa     ... View more