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iTalki affiliate link

The main one.

https://go.italki.com/eigonodo

 

But I can put this after another URL.

/?ref=eigonodo&utm_source=eigonodo&utm_medium=partner&utm_campaign=kol&hl=ja

 

Examples:

Valou

https://www.italki.com/teacher/1069288/?ref=eigonodo&utm_source=eigonodo&utm_medium=partner&utm_campaign=kol&hl=ja

Inest

https://www.italki.com/teacher/8761717/?ref=eigonodo&utm_source=eigonodo&utm_medium=partner&utm_campaign=kol&hl=ja

 

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How to create a first online course on Kajabi

How to create a first online course

Kajabi is very intuitive.  You can start creating something quick and can further develop it into a complex system.  Let’s just start building your first online course.

Click on PRODUCTS (from the left side menu)

Click on New Product (The button at the right-upper side)

Choose Online Course (out of choices)

 

 

 

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Mapping

Sometimes I lose a connection to the share drive at work.  This is how I can fix it.

See below for mapping instructions
1.       Enter “This PC” in the search field, and right click on “This PC” and select Map network drive.
2.      Choose an available drive letter (?) from the dropdown list located next to the "Drive:" option.

 

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Converting Excel files into SAS via. SAS vs. SPSS

I have SAS and SPSS on my PC and have a choice of using SAS or SPSS when converting an Excel file into a SAS dataset.  In terms of reading a date variable, SAS reads the data as is.  SPSS reads it and returns a different value.

This is the original date value for one case in the Excel file.

3/1/2016

SAS PROC IMPORT returned the same date.

01MAR2016

SPSS's IMPORT process (into a SAS dataset) returned this:

02MAR2076

To force SPSS to correct the data, you need to subtract 21916 from the date (which converts the date of this case to be March 1st of 2016).

data spss;set raw.Assessment_spss;
keep DateTaken_74;
FORMAT DateTaken_74 date9. ;
DateTaken_74=DateTaken_74 -21916;
run;

 

Here is the difference in terms of how they read column names.  I read the same Excel table using SAS and SPSS.

SAS PROC IMPORT uses __ (two spaces) when it finds a space in column names.  SPSS ignores spaces.

SAS SPSS
Variable Variable
Site_Name SiteName
Case_Number CaseNumber
Academic_issues__disabled__1066 Academicissuesdisabled_1066
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Survival Analysis using SAS

libname yama "C:\Users\";

data asdf;
set yama.test_data;
OS_length=(OS-toroku_bi)/30.5;
run;

proc lifetest data=asdf;
time OS_length*OS_event(0);
*strata shiken_gun;
run;

proc lifetest data=asdf;
time OS_length*OS_event(0);
strata shiken_gun;
run;

proc lifetest data=asdf;
time OS_length*OS_event(0);
strata PS;
run;

proc phreg data=asdf;
class sex soshiki_gata shiken_gun;
model OS_length*OS_event(0)=shiken_gun sex soshiki_gata PS;
run;

proc phreg data=asdf;
class sex soshiki_gata shiken_gun;
model OS_length*OS_event(0)=shiken_gun;
run;

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R question

I am trying to create this function, but I think the problem parts are where I tried to put macro tokens (e.g., var1, var2, var3) within "".    I'm getting error messages.  Any suggestions welcome.  Rでファンクションを書いているのですが、”　”の間に、var1,var2,var3を入れるとエラーが出ます。どうしたらいいでしょうか？ This is the error message:

Error in eval(cols[[col]], .data, parent.frame()) : 

object 'var3.y' not found

 

<ここから＞

 

make_tables<-function(var1,var2,var3){
analysis_data %>%
mutate(difference=var3.y-var3.x) -> analysis_data_b
analysis_data_c<-filter(analysis_data_b,difference >= 0)

result01pre <-Summarize(var3.x ~ group.x, data= analysis_data_c)
result01pre$test_type<-"Pretest"
result01pre$surveyID<- "var2"
result01pre$tableID<- "var1"
result01pre$item<- "var3.x"
result01pre=subset(result01pre,select=c(tableID, surveyID, item,test_type,group.x,n,mean))

result01post<-Summarize(var3.y ~ group.y, data= analysis_data_c)
result01post$item<- "var3.y"
result01post$test_type<-"Posttest"
result01post=subset(result01post,select=c(item,test_type,group.y,n,mean))

result01diff<-Summarize(difference ~ group.x, data= analysis_data_c)
result01diff$item<- "difference"
result01diff$test_type<-"Difference"
result01diff=subset(result01diff,select=c(item,test_type,group.x,n,mean,sd))

all01<-merge(result01pre,result01post,by.x="group.x",by.y="group.y",all.x = TRUE, all.y = TRUE)
all01<-merge(all01,result01diff,by.x="group.x",by.y="group.x",all.x = TRUE, all.y = TRUE)
#Paired t-test algorithm

all01 %>%
mutate(t_score = (t_score=mean/(sd/sqrt(n)))) %>%
mutate(sig_test=case_when(
t_score < 1.96 ~"ns",
t_score >= 1.96 ~"sig")) ->all01
}}

kaz1 <- make_tables(30,1,miss_5_d_affects_n)