Weight of partitions for pooled solution parameters for conservative or parsimonious solution

wop calculates the contribution or weight of partitions for the pooled solution parameters of consistency and coverage for the conservative or parsimonious solution.

Usage

wop(dataset, units, time, cond, out, n_cut, incl_cut, solution, amb_selector)

Arguments

dataset: Calibrated pooled dataset for partitioning and minimization of pooled solution.
units: Units that define the within-dimension of data (time series).
time: Periods that define the between-dimension of data (cross sections).
cond: Conditions used for the pooled analysis.
out: Outcome used for the pooled analysis.
n_cut: Frequency cut-off for designating truth table rows as observed in the pooled analysis.
incl_cut: Inclusion cut-off for designating truth table rows as consistent in the pooled analysis.
solution: A character specifying the type of solution that should be derived. C produces the conservative (or complex) solution, P the parsimonious solution. See wop_inter for deriving intermediate solution.
amb_selector: Numerical value for selecting a single model in the presence of model ambiguity. Models are numbered according to their order produced by minimize by the QCA package.

Value

A dataframe with information about the weight of the partitions with the following columns:

type: The type of the partition. between stands for cross-sections; within stands for time series. pooled stands information about the pooled data.
partition: Type of partition. For between-dimension, the unit identifiers are listed (argument units). For the within-dimension, the time identifiers are listed (argument time). The entry is - for the pooled data.
denom_cons: Denominator of the consistency formula. It is the sum over the cases' membership in the solution.
num_cons: Numerator of the consistency formula. It is the sum over the minimum of the cases' membership in the solution and the outcome.
denom_cov: Denominator of the coverage formula. It is the sum over the cases' membership in the outcome.
num_cov: Numerator of the coverage formula. It is the sum over the minimum of the cases' membership in the solution and the outcome. (identical to num_cons)

Examples

# load data from Thiem (EPSR, 2011; see data documentation)

data(Thiem2011)
wop_pars <- wop(
  dataset = Thiem2011,
  units = "country", time = "year",
  cond = c("fedismfs", "homogtyfs", "powdifffs", "comptvnsfs", "pubsupfs", "ecodpcefs"),
  out = "memberfs",
  n_cut = 6, incl_cut = 0.8,
  solution = "P",
  amb_selector = 1)
wop_pars
#>       type partition denom_cons num_cons denom_cov num_cov
#> 1   pooled         -      80.64    72.39    101.76   72.39
#> 2  between      1996       7.46     5.49      7.95    5.49
#> 3  between      1997       6.77     5.25      7.95    5.25
#> 4  between      1998       6.79     5.34      7.29    5.34
#> 5  between      1999       7.31     6.31      8.29    6.31
#> 6  between      2000       6.66     6.45      9.91    6.45
#> 7  between      2001       6.80     6.57      9.91    6.57
#> 8  between      2002       6.85     6.59      9.91    6.59
#> 9  between      2003       7.24     7.02     10.13    7.02
#> 10 between      2004       7.73     7.68     11.04    7.68
#> 11 between      2005       8.22     8.09     11.04    8.09
#> 12 between      2006       8.81     7.60      8.34    7.60
#> 13  within        AT       4.32     1.89      2.28    1.89
#> 14  within        BE       9.99     7.71      7.86    7.71
#> 15  within        DE       9.65     9.65     10.73    9.65
#> 16  within        DK       1.73     1.59      7.46    1.59
#> 17  within        ES       8.41     7.95      9.83    7.95
#> 18  within        FI       0.60     0.60      5.26    0.60
#> 19  within        FR       9.88     9.86     10.87    9.86
#> 20  within        GR       1.46     1.29      3.80    1.29
#> 21  within        IE       0.73     0.21      0.21    0.21
#> 22  within        IT       9.21     9.21     10.77    9.21
#> 23  within        LU       0.33     0.33      3.80    0.33
#> 24  within        NL       6.26     5.73      7.06    5.73
#> 25  within        PT       0.81     0.81      3.80    0.81
#> 26  within        SE       6.94     5.27      7.16    5.27
#> 27  within        UK      10.32    10.29     10.87   10.29