Bienmali Kombate

Guangzhou College of Technology and Business · School of Accounting

Hi Folks, I have been strongly with my data, trying to figure out how to gen my crash risk varaible through the NCSKEW method. First of all let me explain my data. My dataset is observations from two years (2019 and 2020) and in each year, each observation is observe only once. I used the average daily price of the stock market Y to compute the return (log Ri = log P1/p0) of firm X on the stock market Y. in addition, because the RM in the dataset was on yearly frequency, I also converted them on daily freqency by dividing each stock market RM on the number of trading days in each year accordingly, and then the average value was log given (log RM). After that I further convert them (daily frequency) in weekly frequency by using the command "ascol logRi, toweek returns(log) " to convert firm x daily return to weekly return and "ascol logRM, toweek returns(log)" to convert stock market Y daily return to weekly return which created respectivelly the variable week_logRi and week_logRM. However, I failed to gen my crash risk variable and will apreciate your assistance and guidance to solve this issue. following the data and commands used bysort ID (Year) : gen t = _n xtset ID t ascol logRi, toweek returns(log) keep(all) ascol logRM, toweek return(log) keep(all) bysort ID (t) : gen F1week_logRM = F1.week_logRM bysort ID (t) : gen F2week_logRM = F2.week_logRM bysort ID (t) : gen L1week_logRM = L1.week_logRM bysort ID (t) : gen L2week_logRM = L2.week_logRM reg week_logRi F2week_logRM F1week_logRM week_logRM L1week_logRM L2week_logR

predict double e, residuals

Error message is given below

reg week_logRi F2week_logRM F1week_logRM week_logRM L1week_logRM L2week_logRM

no observations

r(2000);

. predict double e, residuals

last estimates not found

r(301);

Attached the data

Many thank in advance for your assistance and guidance

Hi Folks.

I am running the moderated mediation of Hayes model 14 using Amos but encounter some difficulties which days ago, I could not manage to fix it.

The difficulty is I have one independent variable and 3 parallel mediators, all moderated on path b by one variable ( the AMOS pathways diagram is included in the attachment file). Therefore to compute the index of moderated mediation and the conditional indirect effect using Amos equivalent to process 14, I ran the syntax that I included in the attachment file, but if keep telling me syntax error with the message shown below the syntax. I have tried everything to fix this issue but couldn't.

Please, I need your guidance.

I really appreciate any help you can provide.

Here are the detailed estimands for the syntax

'<<<BeginOptions>>>

'<<<EndOptions>>>

'<<<BeginStatements>>>

'Moderated mediation using AMOS - Mike Crowson, Ph.D.

'equivalent to Process Model 14

'Simple slopes for X on Mediator at low (mean-1sd), medium (mean), and high (+1sd)

'points along with the moderator (W)

'LowSS=d+j*(mean-1sd on W)

'MedSS=d+j*(mean of W)

'HighSS=d+j*(mean+1sd on W)

'LowSS=e+h*(mean-1sd on W)

'MedSS=e+h*(mean of W)

'HighSS=e+h*(mean+1sd on W)

'LowSS=f+i*(mean-1sd on W)

'MedSS=f+i*(mean of W)

'HighSS=f+i*(mean+1sd on W)

Low1SS=d+j*(11.0708-2.65375)

Med1SS=d+j*(11.0708)

High1SS=d+j*(11.0708+2.65375)

Low2SS=e+h*(11.0708-2.65375)

Med2SS=e+h*(11.0708)

High2SS=e+h*(11.0708+2.65375)

Low3SS=f+i*(11.0708-2.65375)

Med3SS=f+i*(11.0708)

High3SS=f+i*(11.0708+2.65375)

'Conditional indirect effects at different levels of the moderator W

low11CIE=low1SS*a

med11CIE=med1SS*a

high11CIE=high1SS*a

low22CIE=low2SS*b

med22CIE=med2SS*b

high22CIE=high2SS*b

low33CIE=low3SS*c

med33CIE=med3SS*c

hig33hCIE=high3SS*c

'index Of moderated mediation (Hayes, 2015)

indaModMed=j*a

indbModMed=h*b

indcModMed=i*c

'<<<EndStatements>>>

I am looking how to use spss to analyze the regression with primary data.

My research is aimed on 5 variables and the data was collected through a survey questionnaires where each variable composed as follow:  

1st variable (X1) 5 items

2 nd variable (X2) 3 items

3 rd variable (X3) 5 items

4 th variable (X4) 4 items

5 th variable (X4) 5 items

Total items 22

Thanks