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43 Command constructor df$num <- calibrate(df$num, thresholds = "e=35, c=55, i=75")
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45 R console > [1] 2 >
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47 R plot window A simple plot 1: Index
48 Save R plot window 1: A simple plot Index Type: PNG BMP JPEG TIFF SVG PDF File name: Choose directory: root > Users > dusadrian > Work in progress > QCA book + figures book.bib QCAbook.aux QCAbook.bbl QCAbook.blg QCAbook.idx QCAbook.log QCAbook.out QCAbook.pdf QCAbook.tex QCAbook.toc Save
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50 LR AU BE CZ EE FI FR DE GR HU IE IT NL PL PT RO Data editor DEV URB LIT IND STB SURV
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53 Import from text file Separator: comma space tab other, please specify: Decimal: dot comma Column names in the file header No./name of column containing row names Preview column names: Directory: root > Users > dusadrian > Work in progress > QCA boo.. + figures book.bib QCAbook.aux QCAbook.bbl QCAbook.blg QCAbook.idx QCAbook.log QCAbook.out QCAbook.pdf QCAbook.tex QCAbook.toc Assign to: Import
54 Load data from attached packages Package: datasets QCA venn Dataset: HC LC LF LM LR Lipset's indicators for the survival of democracy durng the inter-war period. Help Load
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56 Export to text file Separator: comma space tab other, please specify: Write column names Cases ID: cases Dataset: LR New file: Choose directory: root > Users > dusadrian > Work in progress > QCA book + figures book.bib QCAbook.aux QCAbook.bbl QCAbook.blg QCAbook.idx QCAbook.log QCAbook.out QCAbook.pdf QCAbook.tex QCAbook.toc Export
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59 {a 1 a 2... a n } x 1...n µ A = { 0 / 1
60 : { }
61 3 0 µ A = 1/2 1 { 0 = } 0 n 1 1 n 1 2 n 1... n 1 n 1 = 1
62 3 n n n n n
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66 A B = min(0.8,0.3) = 0.3
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68 A B = max(0.8, 0.3) = 0.8
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76 Calibrate Dataset: LR crisp fuzzy find thresholds jitter points Number of thresholds: 2 Choose condition: DEV URB LIT IND STB SURV th1 550 th2 850 EE calibrate into new condition DEVC Run
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78 Calibrate Dataset: LR crisp fuzzy find thresholds jitter points Number of thresholds: 2 Choose condition: DEV URB LIT IND STB SURV th1 550 th2 850 calibrate into new condition DEVC Run
79 Recode Dataset: LR Choose condition: DEV URB LIT IND STB SURV recode into new condition Old value(s): value lowest to to 851 to highest missing all other values DEVR New value: value missing copy old values Add Remove Clear lo:550=0 551:850=1 851:hi=2 2 Run
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89 Calibrate Dataset: LR crisp fuzzy s-shaped bell-shaped increasing decreasing logistic ecdf 0.95 degree of membership Choose condition: DEV URB LIT IND STB SURV 1.5 e 400 c 550 i calibrate into new condition DEVC Run
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92 0 x e, ( ) b 1 e x 2 e c e<x c, dm x = ( ) a 1 1 i x 2 i c c<x i, 1 x>i. e c i x b a a b a b a b
93 a b
94 1 x i, ( ) a 1 1 i x 2 i c i<x c, dm x = ( ) b 1 e x 2 e c c<x e, 0 x>e. a b a b
95 Calibrate Dataset: LR crisp fuzzy s-shaped bell-shaped increasing decreasing logistic ecdf Shape form: above below 1 1 Choose condition: DEV URB LIT IND STB SURV 1.5 e 400 c 550 i calibrate into new condition DEVC Run p q = p 1 p
96 ( p ) ln 1 p + ( dm ) ln 1 dm
97 ( dm ) ln = dm dm 1 dm = e2.42 dm = e e2.42 dm = 1 1+e = e 2.42 dm = 1 1+e = e
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100 0 x e 1, 1 2 ( e1 x ) b e 1 c 1 e 1 <x c 1, ( ) a 1 1 i1 x 2 i 1 c 1 c 1 <x i 1, dm x = 1 i 1 <x i 2, ( i2 x ) a i 2 c 2 i 2 <x c 2, ( ) b 1 e2 x 2 e 2 c 2 c 2 <x e 2, 0 x>e 2.
101 a b 0 x i 1, ( i1 x ) a i 1 c 1 i 1 <x c 1, ( ) b 1 e1 x 2 e 1 c 1 c 1 <x e 1, dm x = 1 e 1 <x e 2, 1 2 ( e2 x ) b e 2 c 2 e 2 <x c 2, ( ) a 1 1 i2 x 2 i 2 c 2 c 2 <x i 2, 0 x>i 2. Calibrate Dataset: LR crisp fuzzy s-shaped bell-shaped increasing decreasing logistic ecdf Shape form: above below 1 1 Choose condition: DEV URB LIT IND STB SURV 1.5 e1 350 c1 500 i1 650 i2 650 c2 800 e calibrate into new condition DEVC Run
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103 m>0 X>0 p 1 < <p m m φ m (X;β,p)=β 0 + β j X (p j) j=1 X p m (p j ) p =0 ln(x) X 0
104 β j p = β 0 + β 1 ln(x)+β 2 X β 3 X + β 4 X 2
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108 ( TFR= max 0, ) E(x) E(1) 1 E(1)
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110 X Y Y Y X 1 0 X 1
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112 X{1} X{2} Y
113 X Y
114 Y X
115 Y 1 0 a b c d 0 X 1 incln X Y = = +
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117 1 a c e Y 0 b d f 0 1 X 2 incln X{v} Y = v v incln X{2} Y = + +
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119 incln X Y = min( )
120 X Y
121 a c Y Y 0 b d 0 X 1 0 X 1 covn X Y = = +
122 χ 2 χ 2 χ 2 X Y
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125 covn X Y = min( )
126 Y X
127 T nec = RoN = (1 ) (1 min(, ))
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129 A Y B
130 Y A B Y A B
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136 Y X
137 Y Y X 1 0 X 1
138 Y X{1} X{2} Y X
139 Y X
140 Y 1 0 a b c d 0 X 1 incls X Y = = +
141 1 a c e Y 0 b d f 0 1 X 2 incls X{v} Y = v v incls X{2} Y =
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143 incls X Y = min(, )
144 = min(, ) min(,, ) min(,, )
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146 R 2 R 2 R 2
147 Y A B covu A Y = covs A Y covs A B Y covu A Y = min( ) min( ) covu A Y = min( ) min(, max( )
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150 0 X 1 X Y Y 1 0 a b c d b a d c Y Z a b X c e g d f h X Y Z b a d c f e h g
151 2 k 2 3 =8 l k k l k = l 1 l 2 l k i=1 2 3 =2 2 2=8 k
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154 Truth table Dataset: LC LF LM Outcome: DEV URB LIT IND STB SURV Conditions: DEV URB LIT IND STB SURV negate outcome Sort by: cut-off: complete outcome frequency 1 use letters inclusion inclusion 1 1 show cases frequency inclusion 0 deviant cases Assign to: ttlc Run
155 Sort by: Decr. Sort by: Decr. outcome inclusion outcome frequency inclusion frequency
156 2 k 2 k 2 2 =4
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158 2 4 = 16
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160 2 10 = 1024
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169 A B C A B C A B C 1 1 A C
170 A C A B A B C A b C A B c a B c B c
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172 Quine-McCluskey minimization Dataset TT Outcome: Conditions: cut-off: Include? C negate outcome frequency 1 Exclude use letters inclusion 1 1 show cases inclusion 0 maximal solutions Search solutions by: row dominance coverage 1 show details consistency 0 use tilde PI consistency 0 Solution depth 0 PI depth 0 Assign Run
173 LC LF LM Dataset TT Outcome: DEV URB LIT IND STB SURV Conditions: DEV URB LIT IND STB SURV
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175 Quine-McCluskey minimization ttlc Dataset TT Outcome: DEV URB LIT IND STB SURV Conditions: DEV URB LIT IND STB SURV cut-off: Include? C negate outcome frequency 1 Exclude use letters inclusion show cases inclusion 0 maximal solutions row dominance Search solutions by: coverage 1 show details use tilde consistency PI consistency 0 0 Solution depth 0 PI depth 0 Assign to: clc Run Command constructor conslc <- minimize(ttlc, details = TRUE)
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181 Include Exclude? C
182 k
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185 Quine-McCluskey minimization Dataset TT Outcome: Conditions: ttlc ttlf DEV URB LIT IND STB SURV DEV URB LIT IND STB SURV cut-off: Include? C negate outcome frequency 1 Exclude use letters inclusion show cases inclusion 0 Directional exps: DEV URB LIT IND STB maximal solutions Search solutions by: row dominance coverage 1 show details consistency 0 use tilde PI consistency 0 Solution depth 0 PI depth 0 Assign to: plf Run
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189 Empirically observed 1 0 Good Counterfactuals Remainders / Counterfactuals UA Easy Counterfactuals Tenable Assumptions Di cult Counterfactuals Simplifying Assumptions Untenable Assumptions
190 SA = EC + DC
191 X X Y Y X
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197 Quine-McCluskey minimization Dataset TT Outcome: Conditions: ttlc ttlf DEV URB LIT IND STB SURV DEV URB LIT IND STB SURV cut-off: Include? C negate outcome frequency 1 Exclude use letters inclusion show cases inclusion 0 Directional exps: DEV URB LIT IND STB maximal solutions Search solutions by: row dominance coverage 1 show details consistency 0 use tilde PI consistency 0 Solution depth 0 PI depth 0 Assign to: ilf Run
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202 Find incoherent configurations Truth table: ttlc ttlf Select All Expression subsets: remainders only LIT + STB + DEV* URB* IND Contradictory simplifying assumptions Simultaneous subset relations Assign to: INCOH Run Include Exclude? C INCOH
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208 P + N + R = S P N P =4 N =5 4+5+R = S R =3 S S = 12 R S P N R S
209 3 k k
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211 k 3 4 = 81 3 k 3 4
212 3 k 3 3 =
213 A B C D C OUT
214 S l s S MV = k c=1 ( ) c k l s c s=1 3 k 1 3 k S CS = k c=1 ( ) c k 2= c s=1 k c=1 ( ) k 2 c =3 k 1 c
215 A D A D A D A D OUT
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226 X k Z i X k Z i X k Zi X k Z i X k Zi
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236 inclb Xt Y t = N i=1 min( it, it ) it inclw Xi Y i = T t=1 min( it, it ) it
237 T N t=1 i=1 inclp X Y = min( it, it ) min(, ) T N t=1 i=1 = it
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262 incls X Y = min(, ) incls X Y = min(, ) (min(, ) +max(,0)) inclh X Y = min(, ) (min(, ) + max(, 0) )
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272 XY plot Dataset: LC LF LM Inclusion: Coverage: PRI: FR IE SE BE NL UK CZ Condition X: DEV URB LIT IND negate FI Outcome Y: negate LIT IND STB SURV sufficiency necessity parameters of fit show middle guides fill jitter points show case labels rotate SURV HU RO EE PL PT GR IT AU ES URB DE 0.9 1
273 2 k 2 2 =4 2 k 2 k
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280 Venn diagram custom ETHFRACT DEMOC GEOCON AlbaniansFYROM NATPRIDE POLDIS 0 1 C?
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Qualitative Comparative Analysis in Practice: Why, When, and How?
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