About hjjijkkl

hjjijkkl · ‎05-14-2021

Since i have more than 50 variables, how do i keep the observations from those variables from not to show in s_1? for example, ID event date sex 1 6_W 12/3/2010 F 1 8_W 2 6_W 4/7/2012 M 2 8_W 3 6_W 5/8/2012 M 3 8_W 3 10_W So it would look like this below ID event date 1 S_1 12/3/2010 1 6_W F 1 8_W 2 S_1 4/7/2012 2 6_W M 2 8_W 3 S_1 5/8/2012 3 6_W M 3 8_W 3 10_W

hjjijkkl · ‎05-14-2021

Sorry, the outcome will look like this ID event date 1 S_1 12/3/2010 1 6_W 1 8_W 2 S_1 4/7/2012 2 6_W 2 8_W 3 S_1 5/8/2012 3 6_W 3 8_W 3 10_W

hjjijkkl · ‎05-14-2021

I have a big data that looks like this below ID event date 1 6_W 12/3/2010 1 8_W 2 6_W 4/7/2012 2 8_W 3 6_W 5/8/2012 3 8_W 3 10_W I would like to add an observation above every 6_W event called “S_1” and move the date to the new observation. So it would look like this below. How can I do that? ID event date 1 S_1 12/3/2010 1 6_W 1 8_W 2 S_1 4/7/2012 2 6_W 2 8_W 2 S_1 5/8/2012 3 6_W 3 8_W 3 10_W

hjjijkkl · ‎05-10-2021

How can I fi this issue

hjjijkkl · ‎05-10-2021

I am combining two dataset and some of the subjs email address "in the observation" is cutting off when I combine the data. I increased the length but, its not helping at all. the email are all fine before combining the data but, when I combine they are cutting of. Here is an example of the code I used. data need length email $50; set data1 and data2; run;

hjjijkkl · ‎05-06-2021

Can you please give me an example on how to do that? Sorry, I dont have a lot of skills in SAS

hjjijkkl · ‎05-06-2021

the two data are already in SAS stored, I didn't import it.

hjjijkkl · ‎05-06-2021

I am appending two dataset and i am getting this error below. ERROR: Variable age has been defined as both character and numeric. the problem is one of the dataset has missing value and the other data has a numeric value for the same variable (age). what is the best way to solve this issue? below is an example of what the two data look like. Table 1 ID Sex age 1 F . 2 F . Table2 ID Sex age Education 4 M 33 BA 6 F 67 PHD Below is what the data should look like after appending (Table1 and Table2) ID Sex age Education 1 F . 2 F . 4 M 33 BA 6 F 67 PHD

hjjijkkl · ‎05-06-2021

Actually you are rights. I need to append(stack vertically) than merging the two data sets. This an example I can give. ID Sex age 1 F 26 2 F 43 ID Sex age Education 4 M 33 BA 6 F 67 PHD ID Sex age Education 1 F 26 2 F 43 4 M 33 BA 6 F 67 PHD

hjjijkkl · ‎05-06-2021

I have two big datasets and I wanted to compare their variables and merge them. I know there are one or more variables that might be in one or the other. So, I was wondering what is the best way to identify which variables are in common and which variables are in one or the other. After identifying this, I want to merge the two datasets into one dataset. what is the best way to follow and the merging. If someone can show me an example that would be wonderful. Please help! Thank you!

hjjijkkl · ‎04-27-2021

I have a data with variables for day month and year and i want to calculate the age of the subject. id month day year 1 1 27 1985 2 10 12 2002 3 5 20 1990 the output will look like this id Calculated age 1 36 2 18 3 30

hjjijkkl · ‎04-26-2021

From the data below and I am tryign to eliminate those that have two consecutive test above 80. How Do I go about doing My analysis? for example, in the table below, ID R45 will be excluded because it as two test above 80 consecutively (test 90 and test 100). Thanks ID Date test R45 3/15/19 90 R45 4/15/19 100 R45 5/15/19 70 R45 6/15/19 60 R90 3/15/19 12 R90 4/15/19 120 R90 5/15/19 45 R90 6/15/19 100 R30 3/15/19 72 R30 4/15/19 28 R30 5/15/19 50 R30 6/15/19 220 my output would look like this ID Date test R90 3/15/19 12 R90 4/15/19 120 R90 5/15/19 45 R90 6/15/19 100 R30 3/15/19 72 R30 4/15/19 28 R30 5/15/19 50 R30 6/15/19 220

hjjijkkl · ‎04-20-2021

I want to use an if then stament like this below. but, the one i created doesnt work length Yrson 8.; if (time_on_Team)= 'year' then YrsOn= 'Year'; else if (time_on_team)='month' then YrsOn='year'/12; drop time_on_team; label YrsOn = 'Years on Team';

hjjijkkl · ‎04-20-2021

yes

hjjijkkl · ‎04-20-2021

my data is very big but, this is how it looks like ID Time_on_team 1 2years 2 6years 3 6month 4 10years 5 4month 6 8month I am trying to find the range, mean, sd, IQR median for time_on_team

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