Description Format Source References Examples
The data set originates from the Munich founder study. The data were collected on business founders who registered their new companies at the local chambers of commerce in Munich and surrounding administrative districts. The focus was on survival of firms measured in 7 categories, the first six represent failure in intervals of six months, the last category represents survival time beyond 36 months.
A data frame with 1224 observations on the following 16 variables.
Survival of firms in ordered categories
with levels 1
< 2
< 3
< 4
< 5
< 6
< 7
Economic Sector with levels
industry
, commerce
and service industry
Legal form with levels small trade
, one
man business
, GmBH
and GbR, KG, OHG
Location with levels residential area
and
business area
New Foundation or
take-over with levels new foundation
and take-over
Pecuniary reward with levels main
and
additional
Seed capital with levels
< 25000
and > 25000
Equity capital with levels no
and yes
Debt capital with levels no
and
yes
Market with levels local
and
national
Clientele with levels wide
spread
and small
Educational level with
levels no A-levels
and A-Levels
Gender with levels female
and male
Professional experience with levels < 10
years
and > 10 years
Number of employees
with levels 0 or 1
and > 2
Age of the founder at formation of the company
Muenchner Gruender Studie
Bruederl, J. and Preisendoerfer, P. and Ziegler, R. (1996): Der Erfolg neugegruendeter Betriebe: eine empirische Studie zu den Chancen und Risiken von Unternehmensgruendungen, Duncker & Humblot.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## Not run:
data(insolvency)
insolvency$Age <- scale(insolvency$Age)
my_formula <- Insolvency ~ Age + Gender
m_acat <- vglm(my_formula, data = insolvency,family = acat())
m_cratio <- vglm(my_formula, data = insolvency,family = cratio())
m_sratio <- vglm(my_formula, data = insolvency,family = sratio())
m_cumulative <- vglm(my_formula, data = insolvency,family = cumulative())
summary(m_acat)
effectstars(m_acat, p.values = TRUE)
summary(m_cratio)
effectstars(m_cratio, p.values = TRUE)
summary(m_sratio)
effectstars(m_sratio, p.values = TRUE)
summary(m_cumulative)
effectstars(m_cumulative, p.values = TRUE)
## End(Not run)
|
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